# Does the Motor Cortex Want the Full Story? The Influence of Sentence Context on Corticospinal Excitability in Action Language Processing

W. Dupont, C. Papaxanthis, Florent Lebon, Carol Madden-Lombardi

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W. Dupont, C. Papaxanthis, Florent Lebon, Carol Madden-Lombardi. Does the Motor Cortex Want the Full Story? The Influence of Sentence Context on Corticospinal Excitability in Action Language Processing. Neuroscience, 2022, 506, pp.58-67. 10.1016/j.neuroscience.2022.10.022. hal-04185286

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1 Does the motor cortex want the full story? The influence of sentence context
2 on corticospinal excitability in action language processing

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5 Dupont W ¹*, Papaxanthis C ¹, Lebon F ¹#, Madden-Lombardi C ¹²#

6 ¹INSERM UMR1093-CAPS, Université Bourgogne Franche-Comté, UFR des

7 Sciences du Sport, F-21000, Dijon.²Centre National de la Recherche Scientifique
(CNRS), France

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11 # F.L. and C. M-L. equally contributed to this work

12 * Corresponding author: [william.dupont@u-bourgogne.fr](mailto:william.dupont@u-bourgogne.fr)

13
14 Highlights

15 • We studied the effects of action words and sentence context on motor activity.

16 • Corticospinal excitability is modulated by the presence of manual action verbs.

17 • Context helps eliminate residual motor activation when no manual action is present.
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Abstract

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The reading of action verbs has been shown to activate motor areas, whereby sentence context may serve to either globally strengthen this activation or to selectively sharpen it. To investigate this issue, we manipulated the presence of manual actions and sentence context, assessing the level of corticospinal excitability by means of transcranial magnetic stimulation. We hypothesized that context would serve to sharpen the neural representation of the described actions in the motor cortex, reflected in context-specific modulation of corticospinal excitability.

Participants silently read manual action verbs and non-manual verbs, preceded by a full sentence (rich context) or not (minimal context). Transcranial magnetic stimulation pulses were delivered at rest or shortly after verb presentation. The coil was positioned over the cortical representation of the right first dorsal interosseous (pointer finger).

We observed a general increase of corticospinal excitability while reading both manual action and non-manual verbs in minimal context, whereas the modulation was action-specific in rich context: corticospinal excitability increased while reading manual verbs, but did not differ from baseline for non-manual verbs. These findings suggest that sentence context sharpens motor representations, activating the motor cortex when relevant and eliminating any residual motor activation when no action is present.

Keywords: Action language, motor representation, transcranial magnetic stimulation.
39 **Introduction**

Over the past couple of decades, researchers have established a link between
language processes and perceptual-motor processes (Barsalou, 1999, 2008;
Barsalou et al., 2003; Gallese and Lakoff, 2005; Decety and Grèzes, 2006; Zwaan
and Taylor, 2006; Fischer and Zwaan, 2008; Jeannerod, 2008; Glenberg and
Gallese, 2012). More precisely, these authors suggest that the information described
by language would lead to activation in the brain areas that are concerned with the
concept itself; if the concept concerns sight, this will lead to activation in the visual
areas. The same applies to action language, such that semantic information referring
to an action would engage the sensory motor system. While there exist
inconsistencies in the literature suggesting that this distributed activation may be
epiphenomenal at most (Rogers et al., 2006; Patterson et al., 2007; Mahon and
Caramazza, 2008; Lambon Ralph et al., 2009, 2010; Pobric et al., 2010; Mahon,
2015), many researchers would postulate that such activation contributes to
language comprehension.

To better understand this link, researchers have probed the involvement of the
motor system during action language processing using various methodologies, such
as functional Magnetic Resonance Imaging (fMRI) (Hauk et al., 2004; Pulvermüller et
al., 2005; Aziz-Zadeh et al., 2006; Van Dam et al., 2010; although for critical views
see: de Zubicaray et al., 2013; Wurm and Caramazza, 2019),
electroencephalography (EEG) (Pulvermüller et al., 2001; Kellenbach et al., 2002; Xu
et al., 2016), behavioral measures (Pulvermüller et al., 2001; Rabahi et al., 2012,
2013; Andres et al., 2015; Klepp et al., 2019) and Transcranial Magnetic Stimulation
(TMS) (Papeo et al., 2009, 2015; Labruna et al., 2011; Scorolli et al., 2012; Innocenti
et al., 2014; Franklin et al., 2020; see review: Papeo et al. 2013). Specifically, Hauk
et al. (2004) using fMRI reported that silent reading of action words leads to somatotopic activation of the effector-related representation within the primary motor cortex. Papeo et al. (2009) used TMS to observe an increase in MEP amplitude for hand action verbs vs. non-action verbs 500 ms after verb presentation. These cortical activations could explain behavioral modulation during language processing, such as improvement in squat jump (Rabahi et al., 2012, 2013), and facilitation of motor response time (Andres et al., 2015; Klepp et al., 2019).

Such behavioral facilitations are present only if the linguistic content is compatible with the movement performed (Gentilucci et al., 2000; Taylor and Zwaan, 2008; Dalla Volta et al., 2009; Glenberg and Gallese, 2012; Zwaan et al., 2012; Van Dam and Desai, 2017). Furthermore, some studies report decreases in motor activation for action verbs compared to non-action verbs at very early latencies (TMS before end of verb: Buccino et al., 2005), or fail to observe activation of the motor cortex (lexical decision tasks: Perani et al., 1999; Longe et al., 2007; motion word comprehension: Grossman et al., 2002; passive reading: Gianelli et al., 2020). While some of the discrepancies in these findings may be attributable to the timing of these studies (see early interference explanation proposed by Buccino et al., 2005), such results generally undermine the idea that action verbs systematically/automatically activate the motor cortex (see also Rüschemeyer et al., 2007; Raposo et al., 2009). Instead, this activation seems to be, as Kemmerer (2015, page 4) states, "sensitive to attentional and situational factors that we are only beginning to understand."

In our view, context is one of these factors that plays an important role in language processing, allowing a more effective and precise understanding of the action described in the sentence. Indeed, studies using fMRI and behavioral measures demonstrate how context can modulate the degree of motor activation and
89 performance (Raposo et al., 2009; Van Dam et al., 2010; van Dam et al., 2010;
90 Zwaan et al., 2010; Papeo et al., 2012; Van Dam et al., 2012; van Dam et al., 2012;
91 Gilead et al., 2013; Van Dam et al., 2014; Kemmerer, 2015; Beauprez et al., 2018).
92 For instance, Raposo and colleagues (2009) observed activation of motor areas for
93 action verbs in isolation (e.g., *kick*) and in literal phrases (e.g., *kick the ball*), but not
94 in idiomatic phrases (e.g., *kick the bucket*). Likewise, Van Dam et colleagues (2010)
95 observed greater activation in motor-related brain areas for highly specific action
96 verbs (to wave, to wipe) than for less specific action verbs (to greet, to clean).

97 Given these results, it is possible that specifying actions by increasing the
98 sentence context may lead to greater motor cortex activation in general. Indeed,
99 Wurm and Caramazza (2019) report a stronger decoding of action scenes relative to
100 short sentences in frontoparietal representations, which they attribute to a difference
101 in richness of detail. Although motor representations can be triggered by the reading
102 or perception of an action, these researchers suggest that action reading leads to a
103 less specific and robust motor representation. Following this logic, increasing
104 sentence context (specifying the action) could increase motor cortex activation in
105 general, thereby "strengthening" motor representations.

106 Another possibility is that greater sentence context leads to a "sharpening" of
107 motor representations, making them more precise yet not always stronger. This idea
108 is consistent with studies in which the context surrounding action verbs selectively
109 engages motor representations. For instance, Taylor and Zwaan (2008) observed
110 facilitation for rotating a knob when the direction of rotation (clockwise) matched
111 rather than mismatched the direction described in concurrent sentences (*The
112 gardener noticed that the water was still running. He approached the faucet which he
113 turned off quickly*). Interestingly, the motor facilitation was observed at the moment
114 of processing the verb, and reappeared at the post-verbal adverb, only if that adverb
115 qualified the action ("slowly" or "quickly"), and not if the adverb instead shifted focus
116 to the agent (e.g., "obediently" or "eagerly"). This suggests that context can
117 selectively activate motor representations, and furthermore, that these motor
118 representations are temporally pinned to the verb, or any word that draws the
119 contextual focus to the action itself.

120 In the current study, we investigated whether context leads to a general
121 strengthening or a condition-specific sharpening of the motor representations. We
122 used the TMS methodology to probe how context modulated activation in the motor
123 cortex during the reading of verbs. Participants were instructed to read manual-
124 action or non-manual verbs that appeared either in a rich sentential context (full
125 sentence) or in a minimal context (pronoun-verb pair). TMS pulses were delivered
126 over the pointer finger area of the left primary motor cortex at three latencies after
127 verb presentation (200, 300, or 400 ms) to better capture individual corticospinal
128 modulation during reading. We expect to replicate the effect of action often seen in
129 the literature, characterized by a greater corticospinal excitability increase for action
130 compared to non-action sentences. However, this effect may be modulated by
131 sentence context. The strengthening idea would predict greater corticospinal
132 excitability in the rich sentential context than in the minimal context for both manual
133 and non-manual verbs. The sharpening idea, on the other hand, would predict an
134 intensified action effect in the rich context, with an increase of corticospinal
135 excitability for manual verbs but not for non-manual verbs.

136 **Material and method**

137 **Participants**
Thirty-five healthy right-handed adults (12 women; mean age = 23.79 years-old; range 18-29 years) participated in the experiment at the laboratory. As context may have only a subtle effect on the motor system, this sample size was chosen based on a power analysis using a small effect size of 0.25 (G\*Power, version 3.1.9.2., Faul et al., 2007). Handedness was assessed by the Edinburgh inventory (Oldfield, 1971). All participants had normal or corrected-to-normal vision, without neurological, physical and cognitive pathologies. The experiment was conducted in two sessions: 1) an experimental TMS recording and 2) a reading comprehension assessment. Volunteers were first approved for participation by a medical doctor, and confirmed their participation with written consent. The Ethics Committee approved experimental protocol (CPP SOOM III, ClinicalTrials.gov Identifier: NCT03334526) and procedures in accordance with the Declaration of Helsinki.

## Stimuli

One hundred and forty-four French verbs were generated; half referred to *Manual Action* (e.g., “I scrub”) and half were *Non-Manual* (including non-action as “I ignore” as well as actions that did not implicate the hand as “I kick”). These verbs were presented either in a *Rich context* that helped to specify the verb (e.g., “I see a stain on my shirt and I scrub it” or “I see a stain on my shirt and I ignore it”), or in *Minimal context* (e.g., “I scrub” or “I ignore”; see Table 1 for details). Sentences always appeared in the first-person present tense. All rich-context sentences were created such that the target verb occurred at the end of the sentence (see Figure 1). This final pronoun-verb segment was presented alone on a subsequent screen after the beginning of the sentence was presented, thus yielding an identical or very similar presentation screen to the minimal sentence version.
A list was generated, in which 36 of the manual action verbs, and 36 of the non-manual verbs occurred within rich sentence contexts, while the other 36 manual action verbs, and 36 non-manual verbs occurred in minimal sentence context. A second list presented these same verbs in the opposite rich and minimal context versions. Each manual action verb (to scrub) was paired with a non-manual verb (to ignore), sharing the same rich-context sentence (I see a stain on my shirt and I scrub/ignore it), and each verbal stimulus only appeared once in the list. Thereby, across participants, each verb appeared in both conditions, but a given participant saw each verb and each sentence only once. For example, for the scrub/ignore pair, if a given participant read the minimal sentence "I scrub", she/he would also read the rich context sentence "I see a stain on my shirt and I ignore it". And another participant would read "I ignore" as well as "I see a stain on my shirt and I scrub it". In addition, TMS latencies were counterbalanced within each list.

Latent Semantic Analysis (LSA: Isa.colorado.edu; Landauer et al., 1998) was used to assure that manual action verbs (0.294±0.257) and non-manual verbs (0.295±0.269) did not significantly differ in their association scores to the preceding sentence fragments (P=0.868). We also compared various psycholinguistic factors (written frequency, number of characters, and spelling neighbors) between manual action verbs and non-manual verbs using the Lexique.org database (New et al., 2004). Corrected t-tests (modified Hochberg's procedure; Rom, 1990) yielded a significant difference only for written frequency (p=0.004; Mean ratios: 11.34±16.69 and 30.80±53.70 for manual action verbs and non-manual verbs, respectively), but not for number of characters (p=0.604; Mean ratios: 6.37±1.63 and 6.51±1.57 for manual action verbs and non-manual verbs, respectively) nor spelling neighbors (p=0.136; Mean ratios: 5.95±5.03 and 4.73±4.74 for manual action verbs and non-manual verbs, respectively).
manual verbs, respectively). The frequency difference is largely due to a few high-frequency non-manual verbs such as “to read.” Furthermore, as higher frequency would typically increase facilitation and excitability, this difference could only hurt the chances of observing the predicted effect of action. To confirmed the accuracy of the manual and non-manual distinctions of the stimuli, 8 participants were asked to rate on a scale from 1-5 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 manual (4.36±0.34) and non-manual (1.43±0.54) verbs.

Table 1. Example of lexical stimuli used in the experiment. In grey lines are the English translation of the French verbs/sentences presented.

<table><thead><tr><th colspan="2">Manual action</th><th colspan="2">Non-manual</th></tr><tr><th>Minimal Context</th><th>Rich Context</th><th>Minimal context</th><th>Rich context</th></tr></thead><tbody><tr><td>Je mélange</td><td>Les cartes sont sur la table et je les mélange</td><td>Je memorise</td><td>Les cartes sont sur la table et je les mémorise</td></tr><tr><td>I shuffle</td><td>The cards are on the table and I shuffle them</td><td>I memorize</td><td>The cards are on the table and I memorize them</td></tr><tr><td>Je frotte</td><td>Je vois une tache sur mon t-shirt et je la frotte</td><td>J'ignore</td><td>Je vois une tache sur mon t-shirt et je l'ignore</td></tr><tr><td>I scrub</td><td>I see a stain on my shirt and I scrub it</td><td>I ignore</td><td>I see a stain on my shirt and I ignore it</td></tr><tr><td>Je ferme</td><td>L'enveloppe est prête et je la ferme</td><td>Je relis</td><td>L'enveloppe est prête et je la relis</td></tr><tr><td>I close</td><td>The envelope is ready and I am closing it</td><td>I reread</td><td>The envelope is ready and I reread it</td></tr><tr><td>J'accorde</td><td>La nouvelle guitare est très belle et je l'accorde</td><td>J'écoute</td><td>La nouvelle guitare est très belle et je l'écoute</td></tr><tr><td>I tune</td><td>The new guitar is very beautiful and I tune it</td><td>I listen</td><td>The new guitar is very beautiful and I listen to it</td></tr></tbody></table>
<table><thead><tr><th>Je paraphe</th><th>Après avoir lu le<br>contrat, je le paraphe</th><th>Je contemple</th><th>Après avoir lu le contrat,<br>je le contemple</th></tr></thead><tbody><tr><td>I initial</td><td>After reading the<br>contract, I initial it</td><td>I contemplate</td><td>After reading the<br>contract, I contemplate it</td></tr></tbody></table>

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## Procedure

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Participants sat in an armchair. Stimuli were presented on a 19-inch LCD monitor by a home-made software, which controlled TMS triggering and synchronized physiological recordings. Throughout the recording, participants were instructed not to move, while they silently read sentences (passive reading). Corticospinal excitability was recorded at rest, as well as during the reading task at various stimulation latencies (200, 300 or 400ms after the verb onset). These latencies were chosen based on electroencephalogram studies showing 200ms as a minimal latency for semantic processing in anterior regions (Pulvermüller et al., 2001; Hauk et al., 2006). In addition, later latencies are related to changes of P300 in parietal and frontal regions (Pulvermüller et al., 2001), but also N400 in posterior regions (Kellenbach et al., 2002; Beres, 2017) when participants read action words compared to abstract words. In the present study, these different latencies were used to account for individual differences in the speed of semantic integration, which would yield variable peaks of motor cortex involvement.

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Before the experimental trials, the participants performed four familiarization trials, each with a fixation cross, followed by a minimal sentence or a rich sentential context, then a black screen before the next trial. Once the participant understood this procedure, four new practice trials were presented, now including TMS pulses after the appearance of the target verb. Then, the experimental session was divided
220 into 3 blocks, each comprised of 56 trials, yielding 168 trials total in the experiment.

221 Among the 56 trials in each block, 8 trials were interspersed with TMS pulses only at

222 rest (fixation cross), which served as reference stimulations and allowed

223 comparisons across experimental conditions in that block. Therefore, participants
224 saw 48 experimental trials in each of the three blocks, and 144 trials in total.

225 Moreover, to avoid mental fatigue and lack of concentration, there was a two-minute
226 break between each block, allowing participants to be as attentive as possible during
227 experimental blocks. In each block, the number of stimulations was equally
228 distributed between all conditions, but also between the three different stimulation
229 latencies.

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

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232 Figure 1. Experimental procedure. Sentences in a Minimal or Rich context were presented on a screen in

233 front of the participant. Single-pulse TMS was triggered over the left hemisphere and motor-evoked potentials

234 recorded in the right index finger.

234 recorded in the right index finger.
Several weeks later, individuals participated in a second experimental session, in which two levels of contextual reading comprehension ability were assessed. This session was included in order to account for the possible effect of individual differences in the use of context during reading comprehension. To investigate sensitivity to lower-level memory-based context, we administered a "Remember versus Know" paradigm (Tulving, 1985), in which they had to identify whether words were encountered in a previously read text (yes or no response), and in what context they were encountered. To assess higher-level use of context during comprehension, we used a Curriculum-Based Measurement-Maze (Parker et al., 1992), in which readers rely on inferences to select a contextually-appropriate word from three alternatives. After the first sentence, every seventh word in the passage is replaced with that correct word and two distractors. Participants must use the context to select the word that fits best with the rest of the passage.

## TMS

Single-pulse TMS was generated from an electromagnetic stimulator Magstim 200 (Magstim Company Ltd, Whitland) and using a figure-of-eight coil (70 mm in diameter). The coil was placed over the contralateral left hemisphere to target the motor area of the First Dorsal Interosseous (FDI) muscle of the right hand. The coil rested tangential to the scalp with the handle pointing backwards and laterally at a 45° angle away from the midline. First, the mapping of the motor cortex of each participant determined the precise stimulation site (hotspot) corresponding to the location, where the MEPs amplitude of the FDI muscle was the highest and the most consistent for the same stimulation intensity. The resting motor threshold of each participant was determined as the minimal intensity of TMS necessary to induce a MEP of 50µV peak-to-peak amplitude in the right FDI muscle for 4 trials out of 8.
During the experimental session, TMS intensity was set at 130% of the resting motor threshold. This intensity was chosen not only to stimulate the participant above the motor threshold, but also to achieve a stimulus intensity near the middle of the stimulus-response curve (Groppa et al., 2012), from which point it would be possible to observe both increases and decreases in MEP amplitude

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## EMG recording

The EMG signal was recorded through 10mm-diameter surface electrodes (Contrôle Graphique Médical, Brice Comte-Robert, France) placed over the FDI muscle of the right hand. Before placing the electrodes, the skin was shaved and cleaned in order to reduce noise in the EMG signal (< 20µV). The EMG signals were amplified and bandpass filtered on-line (10-1000 Hz, Biopac Systems Inc.) and digitized at 2000 Hz for off-line analysis. We also measured the root mean square of EMG signal (EMGrms), to ensure that participants were at rest in all conditions. Throughout the experiment, EMGrms was monitored for the 100 ms preceding every TMS pulse to ensure complete muscle relaxation, using the following formula (MD = movement duration):

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$$RMS = \sqrt{\frac{1}{MD} \int_{0}^{MD} (EMG)^2 dt}$$

## Data and statistical analysis

EMG data were extracted with Matlab (The MathWorks, Natick, Massachusetts, USA) and we measured peak-to-peak MEP amplitude. We first eliminated outliers for each participant within each stimulation latency and condition; data falling 2 SDs

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above or below individual means for each experimental condition were removed
before analysis (4.13% of total). Then, the average MEP amplitude for each condition
was normalized with reference to baseline MEP amplitude (rest condition):

$$ \left( \frac{Mean condition - Mean rest}{Mean rest} \right) \times 100 $$

Importantly, no analysis on the timing factor was performed as we rather isolated the highest average amplitude (over 12 trials) among the three stimulation times (200, 300, or 400ms) for each participant in each condition. Thus, for each participant, we use the data from only one of these three latencies for each condition, presumably corresponding to the moment when the motor representation was most active. Individuals can vary greatly in speed of decoding, as well as lexical access (Sereno et al., 1998; Dambacher et al., 2006) and semantic integration (Kutas and Hillyard, 1980; Brown and Hagoort, 1993; Van Berkum et al., 1999). In addition, the motor activation that we aimed to measure is likely punctual and fleeting in nature. Therefore, this method of stimulation at multiple latencies after the target verb (informed by previous investigations) was designed to maximize the chances of tapping into the fleeting motor representation, which may might not even be present at all latencies. Selecting only the latency with the highest average MEP helps to account for inter-individual variability in the latency of the motor representation, and its consequential increase in corticospinal excitability. Finally, Grubbs test identified extreme mean values for one participant, who was excluded from the final analysis. All data analyses were performed using the software Statistica (Stat Soft, France).

Data normality was confirmed by the Shapiro-Wilk test. To assess the influence of *Action* and *Context* on corticospinal excitability, we performed a 2 by 2 repeated measures ANOVA with *Action* (Manual action vs. Non-manual) and *Context* (Minimal vs. Rich) as within-subject factors. Then, one-sample t-tests were used to compare
normalized MEPs at zero for each condition to assess whether corticospinal
excitability during reading changed from baseline. Finally, in order to ensure that our
results were not contaminated by muscular pre-activity, we tested with Wilcoxon tests
if the EMGrms before the TMS artifact was not different from zero in our experimental
conditions.

To assess the influence of participants' comprehension ability on their
corticospinal excitability modulations by context, we performed Pearson correlations
between the context effect (Minimal vs. Rich) and the memory-based, as well as the
higher context-level comprehension scores. The data are presented as mean values
(±standard error) and the alpha value was set at 0.05.

## 3. Results

The overall ANOVA revealed a main effect of *Action* ($F_{1,33}$ =4.811, p=0.035, $\eta_p^2$=0.127), with larger MEP ratios for manual action verbs (11.02 ±3.25%) than non-manual verbs (6.76 ±3.19%). We did not observe a main effect of *Context* ($F_{1,33}$ =0.168, p=0.683, $\eta_p^2$=0.005) nor an *Action* by *Context* interaction ($F_{1,33}$ =0.064 p=0.801, $\eta_p^2$=0.001) (Figure 2).

<figure><img src="image_3.png" /><figcaption>Figure 2. Corticospinal excitability in Rich and Minimal Context. Box plots on the left side represent normalized MEPs. The line represents the mean. The box and the whiskers represent the 25th/75th quartile and the 5th and 95th</figcaption></figure>
Using one-sample t-tests, we found that normalized MEPs of all conditions were different from baseline (all p's<0.05), except for non-manual verbs in the rich context (p=0.167). This finding reveals the possible importance of context for reducing residual activation for non-manual verbs that may be unclear in the absence of sentence context.

Low and high-level reading comprehension abilities influenced these outcomes, and in particular the context effect. We observed a positive correlation between the modulations of corticospinal excitability in rich context conditions and the low-level reading comprehension scores (p=0.048; r=0.341). Specifically, higher scores in memory-based comprehension yielded greater corticospinal excitability in rich context conditions but not minimal (p=0.495; r=0.121). This finding reveals that the modulation of corticospinal excitability varies across individuals, and that comprehension ability may partially explain such variability. No significant correlations were observed for the high-level context-based comprehension scores (minimal context: p=0.623; r=-0.087; rich context: p=0.590; r=0.095) (Figure 3). The four correlations were evaluated using the modified Hochberg's correction procedure (Rom, 1990).
<figure><img src="image_4.png" /><figcaption>Higher context-based comprehension scores</figcaption></figure>

<figure><img src="image_5.png" /></figure>

Figure 3. Correlations between the corticospinal excitability modulations depend on the context (Minimal vs. Rich) and the comprehension scores (memory vs. context-level). (A and B) represent correlations between the excitability modulations in Minimal context (A) and Rich context (B) with the memory-based comprehension scores. (C and D) represent correlations between the excitability modulations in Minimal context (C) and Rich context (D) with the higher context-level comprehension scores.

Finally, we analyzed the EMGrms prior to TMS artifacts to test for confounds in MEP modulation. We did not observe any difference between baseline (mean ±SD = 1.76 ±1.06µV) and the other conditions (all p's>0.05; in minimal context, for manual verbs: 1.83 ±1.10µV, for non-manual verbs: 1.84 ±1.13µV; in rich context, for manual verbs: 1.90 ±1.48µV, for non-manual verbs: 1.83 ±1.11µV). This indicates that MEP modulations were not influenced by background EMGrms.

Discussion
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The results of this study support the importance of the type of stimuli in modulating the involvement of the motor cortex during action language processing. We observed action-specific modulation of corticospinal excitability, with increased MEP amplitude for manual action verbs compared to non-manual verbs. Nonetheless, we did not observe a main effect of context nor an interaction between action and context. These findings do not support the "strengthening" idea, whereby sentence context would generate greater motor activation in general. However, there does seem to be some evidence for the idea of "sharpening," as motor activation did not differ from rest when the verb phrase was presented in combination with a sentence context that makes it clear that there is no manual action.

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The activation of the motor cortex is presumed to arise from reading events describing actions, typically verbs. However, even a non-action verb may be able to evoke some degree of motor activation if it is underspecified, because the event representation is vague. Indeed, it seems odd that non-manual verbs presented in a minimal context might increase the corticospinal excitability in hand muscles. However, in the absence of context, it is possible that lexical access to the less constrained meaning evokes a broad distributed activation, including the motor system for some words. Additionally, our non-manual-action verbs included actions that were not manual, and when presented out of context, perhaps these could broadly activate the motor system, including the hand area. Contextual constraints may reduce the possibilities for such broad activation and eliminate unintended meanings. If the verb is well contextualized, the motor representation is more precise, yielding activation of only the appropriate effectors in the motor system that are relevant to the event. This is reflected in our results where all conditions resulted in a higher state of corticospinal excitability from the baseline, except for non-manual
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verbs in the rich context. This suggests that the motor cortex can be automatically
activated at some level even by non-action verbs in the absence of context [see also
motor activation in abstract verbs (Sakreida et al., 2013) and metaphoric sentences
(Desai et al., 2013; Reilly et al., 2019)].

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While we did not observe any boost in motor activation when a rich context
specifies the nature of the described situation, we did observe a lack of residual
motor activation from non-manual verbs for which the representation may have been
unclear in the absence of context. The rich context may lead to a disambiguation of
the meaning of the verb, especially when the verb is vague or has multiple meanings.
This would not apply to all of our stimuli, as for some verb phrases, it was already
clear whether a manual action was implicated or not, even without the context.
However, at least some of our non-manual stimuli were interpreted as implicating
less manual action when presented in combination with a receding sentence context.
Consistent with Mahon and colleagues (Mahon and Caramazza, 2008; Mahon,
2015), motor cortex activation may therefore play an important role in embellishing
certain aspects of word meaning that are relevant in a given context.

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Moreover, an action effect in minimal context is consistent with previous studies
(Papeo et al., 2009; Innocenti et al., 2014), reporting that many manual action verbs
would activate the motor cortex to a greater extent than non-manual verbs without
context. However, we expected a greater difference for these same stimuli if
accompanied by more contextual information to better specify the action, supporting
the sharpening idea. Indeed, the manual nature of the meaning of some verbs is
quite precise regardless of context (e.g., "I write") whereas others can be rather
vague (e.g., "I take"). As mentioned above, this vagueness can even introduce motor
cortex activation in verbs that are intended to be non-action stimuli. Although we did

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not observe a greater effect of action in the rich compared minimal context, further
research is currently underway to further test this idea of sharpening motor activation.

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The present study suggests that the context effect is sensitive to individual
factors, such as memory-based comprehension ability. We found that participants
with higher comprehension ability exhibited a greater increase in excitability when
reading rich-context sentences, regardless of verb type. This does not necessarily
mean that context automatically strengthens motor activity (since no main effect of
context was observed), but rather that the engagement of the motor cortex can vary
across situations and across individuals, and may depend on parameters such as
comprehension ability.

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Based on the current findings and previous studies (Zwaan et al., 2010; Van
Dam et al., 2012; van Dam et al., 2012; Gilead et al., 2013; Van Dam et al., 2014;
Beauprez et al., 2018, 2020; Wurm and Caramazza, 2019), language-induced motor
representations are flexible and at least to some extent sensitive to linguistic context.
It appears that context may play a role in strengthening motor activation for good
comprehenders, as well as eliminating residual motor activation for non-action verbs.
These findings are consistent with cognitive theories that accommodate semantic
flexibility and top-down processes, whereby relevant features and alternative
meanings are determined by the semantic context very early as each new word is
encountered (e.g., Gentner, 1981; Marslen-Wilson, 1987; Tomasino and Rumiati,
2013).

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The question remains as to whether activation of the primary motor cortex is
necessary to process action language (see also: Wurm and Caramazza, 2019).
Researchers observed that disturbances of motor areas caused by repeated TMS

431
during language processing can yield a decrease in performance, implying the engagement of the motor cortex in this process (Willems et al., 2011; Repetto et al., 2013; Vukovic et al., 2017; Courson et al., 2018). While understanding might be disturbed, diminished, or less effective, it is not completely blocked. Although language comprehension may be able to proceed without the involvement of the primary motor cortex, our findings suggest that it may play a role in the optimization of this process, refining linguistic understanding and making it more effective when necessary.

One potential limitation of the current study is the number of experimental trials per participant. Since we cannot know exactly when the motor representation will engage and reach its maximum for each subject, we have to probe at several latencies on separate trials, and select the peak afterwards. This can be considered a strength of our study in that we consider individual differences in processing time, but it can also be a limitation in that we reduce the number of experimental trials. In future investigations, we plan to overcome this limitation by calibrating each subject's individual processing time prior to the test session, as well as employing continuous measures, such as EEG. Finally, while we strove to maximize the control between the rich and minimal context conditions, we could not avoid the additional pronoun which sometimes preceded the verb in the rich context condition. When this occurred, the target verb was rendered grammatically transitive in the rich context (*Je le frotte*; I scrub it) while it remained intransitive in the minimal context (*Je frotte*; I scrub). Otherwise, the probe screens were identical for the two conditions.

In conclusion, this study provides relevant information about the role of sentential context on primary motor cortex activation. We found that linguistic context serves to focus the motor representation of the described action, eliminating residual
motor activation for non-action verbs. Moreover, the context effect appears to be sensitive to individual differences in reading comprehension. Consistent with the idea of semantic flexibility and top-down processes, when target verb phrases are presented with a sentence context that makes it clear that no manual action is evoked, the motor cortex does not contribute to the meaning representation.

### Declaration of competing interest

None declared.

### Author Contributions

Experiment design: WD, CML, FL, CP

Data collection: WD

Statistical analysis: WD, CML, FL

Manuscript preparation: WD, CP, CML, FL

### Data availability statement.

All data from this study are available at

https://osf.io/5zbmq/?view_only=82c93af470fd42be8ca33969b14f1c37

### Acknowledgement

The authors are very grateful to Cyril Sirandré for help with the custom Neurostim software and the experimental setup.

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