Theories about embodiment of language hold that when you process a word’s meaning, you automatically simulate associated sensory input (e.g., perception of brightness when you process lamp ) and prepare associated actions (e.g., finger movements when you process typing ). To test this latter prediction, we measured pupillary responses to single words that conveyed a sense of brightness (e.g., day ) or darkness (e.g., night ) or were neutral (e.g., house ). We found that pupils were largest for words conveying darkness, of intermediate size for neutral words, and smallest for words conveying brightness. This pattern was found for both visually presented and spoken words, which suggests that it was due to the words’ meanings, rather than to visual or auditory properties of the stimuli. Our findings suggest that word meaning is sufficient to trigger a pupillary response, even when this response is not imposed by the experimental task, and even when this response is beyond voluntary control.

Theories about embodiment of language hold that when people process a word’s meaning—at least for words that refer to concrete actions or objects—they mentally simulate what they can do with the word’s referent and what this referent looks, smells, and feels like. For example, according to such theories, when people read the word keyboard, they mentally simulate a typing action, and when they read the word sun, they simulate the perception of a bright ball of fire in the sky. Theories positing strong embodiment of language hold that such simulations are necessary for comprehension; that is, to understand what sun means, people would need a sensory representation of what it looks like (Glenberg & Gallese, 2012; Pulvermüller, 2013). By contrast, theories suggesting weak embodiment of language are a middle ground between strong embodiment and the traditional view of language as a purely symbolic system that does not involve sensory and motor representations: According to theories suggesting weak embodiment of language, simulations may facilitate language comprehension but are not strictly necessary; that is, mentally picturing the sun may help someone to read sun faster, but they could understand sun, even without any sensory representation of it, by relying on a symbolic system (Meteyard, Cuadrado, Bahrami, & Vigliocco, 2012; Zwaan, 2014). As critics of embodied cognition have pointed out, by admitting that sensory simulations may not be necessary for language comprehension, weakly embodied views of language are fundamentally different from strongly embodied views and, in some ways, are similar to traditional, symbolic views of language (Bedny & Caramazza, 2011; Mahon, 2015; Mahon & Caramazza, 2008).

Most support for sensory and motor simulations during language comprehension comes from studies that have taken one of two general approaches: behavioral studies that look at compatibility effects between word meaning and action (or perception; Aravena et al., 2012; Glenberg & Kaschak, 2002; Kaschak et al., 2005; Meteyard, Bahrami, & Vigliocco, 2007; Meteyard, Zokaei, Bahrami, & Vigliocco, 2008; Zwaan, Madden, Yaxley, & Aveyard, 2004; Zwaan & Taylor, 2006) and neuroimaging studies that compare brain activity during language comprehension with brain activity during action (or perception; Dravida, Saxe, & Bedny, 2013; Hauk, Johnsrude, & Pulvermuller, 2004; Revill, Aslin, Tanenhaus, & Bavelier, 2008). A compelling example of a behavioral-compatibility effect was reported by Meteyard and her colleagues (2008), who found that upward-downward visual motion affects comprehension speed of words that have a meaning related to upward-downward motion (see also Kaschak et al., 2005; Meteyard et al., 2007); that is, participants decided more quickly that fall was a real word (as opposed to a nonword) when they simultaneously saw downward-moving dots. From this, Meteyard et al. (2008) concluded that understanding words that have a meaning related to upward-downward motion involves, at least in part, the same brain areas as perceiving downward motion. This conclusion is supported by neuroimaging studies that show overlap in the brain areas that are active during both (a) reading of words associated with motion and (b) perception of motion (Revill et al., 2008; but for the limits of this overlap, see Dravida et al., 2013).

However, behavioral studies have so far not directly tested one of the central predictions of embodied language: that word meaning by itself can trigger, at least in some cases, associated involuntary actions. For example, consider a landmark study by Glenberg and Kaschak (2002) in which participants judged whether sentences were sensible or not. These sentences conveyed a movement toward or away from the body (e.g., “open the drawer” for movement toward and “close the drawer” for movement away from the body), and participants responded by moving their hands either toward or away from their bodies (e.g., toward themselves for sensible sentences and away from themselves for nonsensible sentences, or the other way around). The crucial finding was that responses were fastest when the direction of the response coincided with the movement direction implied by the sentence; that is, when participants read “open the drawer,” they were fastest when they responded with a movement toward the body. This showed that word meaning can modulate actions. However, in this experiment, word meaning did not trigger actions; rather, word meaning sped up (or slowed down) actions that were imposed by the task. To our knowledge, the same is true for all behavioral studies that have investigated the effect of word meaning on action. These studies demonstrate (sometimes very convincingly) that word meaning can modulate actions (e.g., grip force, Aravena et al., 2012) or speed up manual responses (Glenberg & Kaschak, 2002; Zwaan & Taylor, 2006), but not that word meaning can by itself trigger an action.

In the current study, we aimed to show that word meaning by itself can trigger a pupillary light response, an involuntary movement that has traditionally been believed to be a low-level reflex to light. However, recent studies have shown that the light response, although beyond direct voluntary control, is sensitive to high-level cognition (reviewed in Binda & Murray, 2014; Mathôt & Van der Stigchel, 2015). For example, pupils constrict when people covertly attend (without looking at it) to a bright object compared with a dark object (Binda, Pereverzeva, & Murray, 2013; Mathôt, van der Linden, Grainger, & Vitu, 2013; Naber, Alvarez, & Nakayama, 2013). Likewise, pupils constrict when people imagine a bright object (Laeng & Sulutvedt, 2014) or when a bright object reaches awareness in a binocular-rivalry paradigm (Naber, Frassle, & Einhauser, 2011). These phenomena are often explained in terms of top-down modulation of visual brain areas (Mathôt, Dalmaijer, Grainger, & Van der Stigchel, 2014; Wang & Munoz, 2016); that is, pupils constrict when people covertly attend to a bright object, because attention enhances the representation of the bright object throughout visual cortical and subcortical areas.

This reasoning can be naturally extended to embodied language: If word comprehension activates brain areas known to be involved in processing of nonlinguistic visual information (i.e., creates sensory representations), then understanding words that convey a sense of brightness or darkness should trigger pupillary responses—just like attending to (Mathôt et al., 2013) or imagining (Laeng & Sulutvedt, 2014) bright or dark objects. Phrased differently, if words that convey brightness trigger a pupillary constriction relative to words that convey darkness, this would support the view that word comprehension affects sensory brain areas and can even trigger involuntary (pupillary) responses. To our knowledge, this would also be the first direct demonstration that word comprehension by itself can trigger a response and not merely modulate an action that has been imposed by task instructions.

To test this hypothesis, we conducted two main experiments in which participants read (visual experiment) or listened to (auditory experiment) words conveying brightness or darkness. We measured pupil size and predicted that pupils would be smaller when participants read or listened to words conveying brightness than when they read or heard words conveying darkness: a pupillary light response triggered by word meaning.

Method Stimuli For the main experiments, in which we varied the semantic brightness of words (i.e., whether words conveyed brightness or darkness), we manually selected 121 words from Lexique (New, Pallier, Brysbaert, & Ferrand, 2004), a large database with lexical properties of French words. There were four word categories: words conveying brightness (e.g., illuminé or “illuminated”; n = 33), words conveying darkness (e.g., foncé or “dark”; n = 33), neutral words (e.g., renforcer or “to reinforce”; n = 35), and animal names (e.g., lapin or “rabbit”; n = 20). During the visual experiment, words were shown as dark letters (8.5 cd/m2) against a gray background (17.4 cd/m2). For the auditory experiment, words were generated in a synthetic voice by using the Mac OS X “say” command to convert text to speech. Because we wanted to compare pupillary responses to words conveying brightness or darkness, these two categories needed to be matched as accurately as possible. We focused on two main properties: lexical frequency, or how often a word occurs in books (words conveying brightness: M = 41 per million, SD = 147; words conveying darkness: M = 39 per million, SD = 119), and, for the visual experiment, visual intensity (words conveying brightness: M = 1.58 × 106 arbitrary units, SD = 4.31 × 105; words conveying darkness: M = 1.56 × 106 arbitrary units, SD = 4.26 × 105). Visual intensity was matched by selecting words that had approximately the same number of letters, then generating images of these words, and finally iteratively resizing these images until the visual intensity (i.e., summed luminance) of the words was almost identical between the two categories. In the end, we had a stimulus set in which words conveying brightness or darkness were very closely matched; however, as a result of our stringent criteria, our set contained several variations of the same words, such as briller (“to shine”) and brillant (“shining”). But given pupils’ sensitivity to slight differences in task difficulty (i.e., lexical frequency) and visual intensity, we felt that matching was more important than having a highly varied stimulus set. For the control experiment, in which we varied the valence of words, we selected 60 words that were rated for valence by Bonin et al. (2003), complemented with the 20 animal names selected for the main experiments. Positive words (e.g., cadeau or “present”; n = 30) had a valence of at least 3.5 on a scale from 1 (negative) to 5 (positive), and negative words (e.g., cicatrice or “scar”; n = 30) had a valence of 2.5 or less. The positive and negative words were matched on lexical frequency (positive: M = 3.21, SD = 0.76; negative: M = 3.26, SD = 0.53) and visual intensity (positive: M = 1.15 × 106, SD = 3.47 × 105; negative: M = 1.15 × 106, SD = 3.48 × 105), and none of the words had any obvious association with brightness or darkness. For all experiments, stimuli were manually selected on the basis of strict criteria. Our sample size of around 30 words per condition was therefore a compromise between having well-matched stimuli and having a reasonable number of observations per participant and condition. Pupillometry experiments Thirty naive observers (age range: 18–54 years; 21 women, 9 men) participated in the visual experiment. Thirty other naive observers participated in the auditory experiment (age range: 18–31 years; 19 women, 11 men). Finally, 30 naive observers participated in the control experiment, four of whom had also participated in the auditory experiment (age range: 18–31 years; 19 women, 11 men). We used two to three times as many participants per experiment as in most previous studies on the pupillary light response (e.g., n = 5–15 participants in Binda et al., 2013; Mathôt et al., 2013, but 52 participants in Experiment 5 of Laeng & Sulutvedt, 2014), because we expected the effect of embodied language on pupil size to be relatively small. Participants reported normal or corrected vision, provided written informed consent before the experiment, and received €6 for their participation. The experiment was conducted with approval of the Comité d’éthique de l’Université d’Aix-Marseille (Ref. 2014–12–03–09). Pupil size was recorded monocularly with an EyeLink 1000 (SR Research, Mississauga, ON, Canada), a video-based eye tracker sampling at 1000 Hz. Stimuli were presented on a 21-in. CRT monitor (screen resolution: 1,024 × 768 pixels; refresh rate: 150 Hz; model p227f, ViewSonic, Walnut, CA). Testing took place in a dimly lit room. The experiment was implemented with OpenSesame (Mathôt, Schreij, & Theeuwes, 2012) using the Expyriment (Krause & Lindemann, 2014) back end. At the beginning of each session, a nine-point eye-tracker calibration was performed. Before each trial, a single-point recalibration (drift correction) was performed. Each trial started with a dark central fixation dot on a gray background for 3 s. Next, a word was presented. In the visual experiment and the control experiment, the word was presented in the center of the screen for 3 s or until the participant pressed the space bar; in the auditory experiment, the word was played back through a set of desktop speakers, and the experiment paused for 3 s or until the participants pressed the space bar. The participants’ task was to press the space bar whenever they saw or heard an animal name and to withhold response otherwise. Participants saw or heard each word once, with the exception of pénombre in the visual experiment.1 Word order was fully randomized. Normative ratings For all words conveying brightness or darkness, we collected normative ratings from 30 naive observers (age range: 18–29 years; 17 women, 13 men), most of whom had not participated in the pupillometry experiments. Participants received €2 for their participation. Words were presented one at a time and using the same images used for the visual pupillometry experiment, together with a five-point rating scale. On this scale, participants indicated how strongly the word conveyed a sense of brightness (from very bright to very dark) or the word’s valence (from very negative to very positive). Brightness and valence were rated in separate blocks, the order of which was counterbalanced across participants. On the basis of valence ratings, we calculated the emotional intensity of the words as the deviation from neutral valence (intensity = |3 – valence|).

Action Editor

Matthew A. Goldrick served as action editor for this article. Declaration of Conflicting Interests

The authors declared that they had no conflicts of interest with respect to their authorship or the publication of this article. Funding

This research was funded by Marie Curie Action 622738 and Nederlandse Organisatie voor Wetenschappelijk Onderzoek VENI Grant 451-16-023 (to S. Mathôt) and by Marie Curie Action 302807 (to K. Strijkers). The research was also supported by Grants 16-CONV-0002 (to the Institute for Language Communication and the Brain) and 11-LABX-0036 (to the Brain and Language Research Institute) from the Agence Nationale de la Recherche. Supplemental Material

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Notes 1.

Because of a bug in the experiment, the word pénombre was shown twice; this is why there were slightly more words conveying darkness than words conveying brightness.