Brain Signatures of Embodied Semantics and Language: A Consensus Paper

What Kind of Neural Evidence is There for Embodied Semantics?

Understanding the neural bases of embodied semantic processing requires the identification of the neurobiological markers that can be associated with sensorimotor simulation of linguistic meanings. This is a fundamental step towards developing theories of how embodied semantics is implemented at the level of neural circuits, as well as to make explicit predictions about the outcomes of experiments. In this section, we will review findings from different neuroimaging techniques that have contributed to the identification of distinct neural indices of sensorimotor simulation. For each methodological approach, we will address candidate mechanisms underlying the simulation of both the sensorimotor (e.g., recruitment of the motor system) and purely sensory (e.g., recruitment of the visual system) aspects of linguistic meanings.

Neuroanatomically, a number of findings supporting embodied meaning representations have primarily been based on a localization approach, aimed at estimating cortical structures activated during word comprehension outside core language areas. Such studies, for instance, showed that accessing the meaning of linguistic material is supported by the sensorimotor system. For example, a number of experiments showed that effector-specific cortical premotor and primary motor regions are recruited when individuals process words or sentences referring to actions carried out with different body parts (Aziz-Zadeh et al., 2006; Boulenger et al., 2009; Ge et al., 2018; Hauk et al., 2004; Kemmerer et al., 2008; Rüschemeyer et al., 2007; Tettamanti et al., 2005; but see Postle et al., 2008). Similarly, sensory brain regions were also found to activate during semantic processing. For example, processing words whose meaning is associated with auditory experiences (e.g., telephone) led to a larger brain activation in auditory areas compared to the processing of words denoting visual features (e.g., moon; Kiefer et al., 2008). Similarly, words referring to so-called multimodal concepts, that is, concepts that can be experienced through different modalities (e.g., playing) activate different modality-specific networks (i.e., visual and action-related; Van Dam et al., 2012).

These latter findings have led researchers to ask how semantic information distributed across different networks becomes integrated into coherent representations. Studies targeting this question have hypothesized the existence of convergence zones (Barsalou et al., 2003; Damasio et al., 2004) and one or several semantic hubs (Patterson et al., 2007), that is, central processing nodes that unify information from multiple networks into a coherent semantic representation. By means of a neurocomputational model it was shown that distributed circuits in hub areas can link motor and sensory semantic information (Tomasello et al., 2017); the authors suggested that semantic processing is distributed across category-general hubs as well as category-specific areas. Among others, the anterior temporal lobe (Lambon Ralph et al., 2010) and the parahippocampal gyrus (Epstein & Kanwisher 1998) have been proposed as candidate regions to bind and coordinate multiple representations. Yet, the exact contribution of these regions to semantic processing and the mechanisms that underpin it remain poorly understood.

Overall, the neuroimaging studies mentioned above (along with many others) provide some support for the claim that, at least in some contexts, conceptual language representations and sensorimotor processes are based on partially overlapping brain resources. Yet, to what extent the sensorimotor system supports meaning processing is still matter of debate. Moreover, the underlying computations performed by sensorimotor regions should still be at least to some degree distinct for language vs. sensorimotor processing. Thus, one future challenge for embodied semantics theories is to explain the dynamics that allow a given brain region to carry both conceptual and sensorimotor processing. Recent investigations of visual processing and imagery using laminar functional magnetic resonance imaging (fMRI), a neuroimaging tool capable of structural resolution at level of cortical layers, have shown that bottom-up sensory signals (visual input) and internally generated signals (e.g., visual imagery) are distributed across different laminar profiles (Lawrence et al., 2018). Extending these cases to language processing, sensorimotor simulation signals generated during word comprehension could be dissociated from sensory processing in terms of their laminar profile. Future studies using imaging techniques with laminar-resolved resolution are needed to assess how the same cortical circuit can process both sensory input and store word meanings at the same time. Similarly, comparing the processing of the same stimulus content presented in different modalities (i.e., linguistic and sensory) with time-resolved techniques may provide novel insights about the differences that characterize the semantic engagement from the perceptual-motor one (e.g., Giari et al., 2020).

Electroencephalography ([EEG]; Alemanno et al., 2012; Moreno et al., 2015; van Elk et al., 2010), magnetoencephalography ([MEG]; Niccolai et al., 2014) as well as electrocorticography (Canolty et al., 2007) studies have attempted to find electrophysiological markers of embodied semantics by looking at the oscillatory properties of the brain signal accompanying lexical-semantic language processing. Research concerning motor simulation has so far focused on embodied processes related to the visual or auditory presentation of single verbs or verbs embedded in sentences and associated with motor experience. Overall, results point to a specific role of oscillatory brain signals in certain frequency bands (i.e., alpha, beta, and closely related mu-rhythm) in implementing sensorimotor simulations. In particular, beta desynchronization (power suppression within the 13–30 Hz frequency range) was suggested as a candidate mechanism supporting the reactivation of motor experience during semantic processing, given its well-known role in preparation and execution of movements (Babiloni et al., 2002; Doyle et al., 2005; Koelewijn et al., 2008; Pfurtscheller & Lopes da Silva, 1999) as well as in isometric contraction of different body muscles (Tecchio et al., 2008). This has encouraged studies to investigate beta oscillations in the context of linguistic action processing in order to determine whether this activity pattern may constitute a neurophysiological marker of embodiment processes in other sensory modalities as well (e.g., auditory, see Niccolai et al., 2020). Results showed that loud actions induced significantly stronger beta power suppression compared to quiet actions in the left auditory cortex.

Along with beta suppression, the suppression of mu (8–13 Hz) rhythm, found over the sensorimotor cortex, is thought to reflect neural activity in the motor and premotor cortex and be associated with performing and observing movement (Caetano et al., 2007; Pfurtscheller & Lopes da Silva, 1999), motor imagery (Matsumoto et al., 2010), and, importantly, action language processing (Fargier et al., 2012). For instance, mu suppression has been observed during the processing of action-related sentences, during the retrieval of lexical-semantic information (van Elk et al. 2010), and in priming tasks using action words in first and second languages (Vukovic & Shtyrov, 2014). Somatotopic mu suppression has been observed while participants read single verbs related to the body (Niccolai et al., 2014); crucially, action language appears to produce greater mu suppression compared to abstract language (Alemanno et al., 2012; Moreno et al., 2015). However, a consensus has yet to be reached regarding the functional interpretation of mu-band activity suppression. Whereas some previous studies associated it with motor-cortex activity, the mu frequency band (8–13 Hz) overlaps with the alpha frequency band (8–12 Hz). While some authors claim that the two rhythms may be confounded (Hobson & Bishop, 2016), others argue that mu frequency reflects the functional state of the motor and premotor cortex and can be dissociated from occipital alpha by its fronto-central topography (Moreno et al., 2015) and motor-cortex localization of its sources (Vukovic & Shtyrov, 2014).

Concerning the generation of perceptual (rather than motor) simulation, a candidate mechanism to implement the simulation of perceptually based concepts (e.g., red or triangle) might be reflected by alpha-band oscillations. In visual perception, increases of alpha synchronization in occipital regions have been largely associated with top-down object-knowledge activation and maintenance during attention, prediction, and working memory tasks (Worden et al., 2000; Snyder and Foxe, 2010; Mayer et al., 2015; Jensen et al., 2002). Alongside its well-known role as inhibitory filter, current models of alpha oscillations posit that enhancement of neural alpha synchronization might reflect selective amplification of neural representations of object categories in task-relevant sensory regions (Palva & Palva, 2007; Klimesch, 2012; van Kerkoerle et al., 2014; Mo et al., 2011). Under this account, neural alpha synchronization might reflect a candidate mechanism to also implement language-mediated perceptual simulations. Although enhancements of neural alpha synchronization have not been reported ubiquitously during word processing, they have been consistently found in studies that used paradigms in which sensory processes are involved in language comprehension (e.g., word-picture matching task, sentence-shape verification task). Such tasks are particularly suited to assess the neural underpinnings of embodied semantic processing, as they require participants to mentally simulate the perceptual content of a given word or utterance to detect or recognize its referent. For instance, EEG studies have shown that processing spoken and written language material can facilitate the recognition of object categories and ambiguous images (Samaha et al., 2018; Morucci et al., 2021). Crucially, this facilitation is associated with an increase in posterior alpha synchronization in the time interval between the cue and the target image. The amplitude of alpha oscillations also seems relevant to object recognition processes, as it correlates with reaction times and early event-related components such as the P1 (Samaha et al., 2018; Mayer et al., 2015). These findings provide some support for the fact that alpha oscillations might reflect a mechanism to carry language-generated object representations in visual regions, mirroring the computational role that alpha waves play in visual perception (Palva & Palva, 2007; Klimesch, 2012; van Kerkoerle et al., 2014; Mo et al., 2011).

Oscillatory signatures of situated/embodied linguistic processes have also been found for more complex functions, outside basic sensorimotor modalities. For instance, it has been shown that comprehension of spatially-related language recruits brain mechanisms involved in navigation and spatial cognition (Vukovic & Shtyrov, 2017). This study used EEG to estimate activity in alpha/mu and beta ranges in both a spatial navigation task and a language task, which involved comprehension of sentences related to perspective/reference-frame concepts, and found a shared network of distributed cortical generators activated for both tasks, which, furthermore, was specific to individual navigation preferences.

Apart from oscillatory activity, a plethora of electrophysiological studies investigated the time course and magnitude of linguistic embodiment by means of event-related potentials (ERPs) or fields (ERFs), most notably focusing on sensorimotor areas (e.g., Dalla Volta et al., 2014; Hauk & Pulvermüller, 2004; Klepp et al., 2014). Neurophysiological studies point to sensorimotor effects occurring between 80 and 350 ms accompanying the processing of single verbs as well as of action words embedded in sentences (Boulenger et al., 2012; Pulvermuller et al., 2005; Shtyrov et al., 2014). Some neurophysiological investigations complement behavioral measures of verbal-motor interaction (for a review, see Fischer & Zwaan, 2008) as well as priming and interference effects (for a review, see Garcia & Ibanez, 2016). Action-related words, for example, induced larger mismatch negativity-like ERPs when presented in body-part-incongruent sound contexts (e.g., kiss in footstep sound context) than in body-part-congruent contexts (e.g., kick in footstep sound context; Grisoni et al., 2016). In another study, finger button presses prior to the presentation of an arm-related word (e.g., stir) resulted in reduced brain activity in the hand knob compared to the incongruent conditions (e.g., jump), the related latency of 150 ms suggesting early semantic information retrieval (Mollo et al., 2016). Overall results from EEG and MEG show early and ultra-early effects of verb processing on sensorimotor areas as well as modulatory effects of motor priming or interference on cortical motor activation related to word processing. Furthermore, such effects have been documented even when the participants’ attention was diverted away from the linguistic input, suggesting a large degree of automaticity of sensorimotor involvement in language processing (Grisoni et al., 2016; Shtyrov et al., 2004, 2014). Still, behavioral effects of congruency between body-related action verbs (hand, foot) and body effector used for responses were shown to be larger when lexical decision or physical judgments tasks were performed, thus pointing to a role of attention and depth of processing in embodiment (Miller & Kaup, 2020). Also, semantic motor priming was shown to be effective only when a semantic task was required and not when semantic processing could be ignored (Klepp et al., 2017).

Potential ERP correlates of sensory simulation during language processing can also be found when examining the effects of language on visual perception. A critical question concerning language-perception interactions is whether language affects visual processing at early stages (i.e., by modulating activity in early sensory regions) or at later semantic or decision-making levels. The rationale of these studies is that, if words or utterances activate sensory representations of their referent objects in early sensory regions, then such representations should modulate early ERPs such as the P1 or N1 – putatively considered an electrophysiological index of low-level visual processes (Spehlmann, 1965). If, however, language only activates amodal representations, then no early sensory modulations should be found. Instead, later ERP effects might be found, such as the N400, typically associated with higher levels of object recognition. Studies using word-picture matching tasks showed that single words can bias visual processing of object categories as early as 100 ms from the onset of the image, with such modulations arising primarily in occipital regions (Boutonnet & Lupyan, 2015; Noorman et al., 2018). Similarly, processing words referring to facial body parts (e.g., nose) increases the amplitude of the N170 in the face-processing system to a larger extent than other body parts (e.g., hand). Interestingly, a machine-learning classifier trained to discriminate between facial body and non-facial body parts achieved better performance when trained on data from the face-processing system in the first 200 ms after word onset, compared to data based on the multimodal-network after 250 ms (Garcia et al., 2020). These findings suggest that at least some categories of content words activate content-specific visual representations in early sensory regions. Similar effects have also been reported when sentences precede visual object category presentation. For instance, hearing sentences about faces influences face processing by modulating the N170 component (Landau et al., 2010). Similarly, Hirschfeld et al. (2011) showed that ERP responses generated by incongruent sentence-picture pairs differed from those generated by congruent pairs around 170 ms after picture onset. Interestingly, studies using interference paradigms showed that visual noise disrupts the processing advantage for congruent word-picture pairs (Edmiston & Lupyan, 2017), but not for congruent sentence-picture pairs, which are instead affected by semantic noise (Ostarek et al., 2019). This finding suggests that while the processing of single words can lead to the activation of visual information, larger language units (e.g., sentences) might rely more on amodal knowledge representations. This is in line with models in which language comprehension engages two complementary systems, a perceptual and an abstract one (Mahon & Caramazza, 2008; Hirschfeld, 2011; Bi, 2021).

The functional relevance of modality-specific activation for the understanding of linguistic meanings remains a controversial issue. Theoretical models provide different views on the extent to which sensorimotor simulations contribute to semantic comprehension, with some theories claiming that simulations are necessary for language comprehension (Pulvermüller, 1999), others suggesting that they are context-dependent (Barsalou, 1999), and others limiting their functional role (Mahon & Caramazza, 2008). Causal paradigms provide some appealing methods to address this problem (See Ostarek & Bottini, 2021 for a review). These paradigms include studies on sensory and motor impaired individuals (e.g., blind or deaf individuals), lesion studies, and stimulation studies.

Studies on individuals with sensory and motor impairments provide a critical test for embodied semantics. The logic of these studies is straigthforward: if understanding the meaning of motor- (e.g., kick) or vision-related language (e.g., sky) requires the recruitment of motor and visual simulations respectively, then individuals with impaired motor or visual abilities should have a deficit in processing this type of language material. Evidence from these paradigms, however, is intermixed. For instance, processing action verbs activates the left middle temporal gyrus in both sighted and congenitally blind individuals (Bedny, Caramazza, Pascual-Leone, & Saxe, 2012), suggesting that the lack of visual experience does not impair semantic processing. Specifically, these findings have been taken as evidence for the fact that brain regions putatively activated during the processing of action verbs may represent amodal representations of verb meanings instead of visual-motion simulations. On the other hand, there is some evidence that specific dimensions of meaning, such as color concepts (e.g., “blue”), may be represented in different regions in sighted and blind people. For instance, while processing color words activates regions known to represent low-level visual features (e.g., the posterior occipital cortex) in sighted people, individuals born blind seem to rely more on temporal regions, that is, regions usually associated with lexical-semantic processing (Bottini et al., 2020). This latter result suggests that sensory simulations may be recruited during the processing of some specific meanings, but that they are not necessary, or always available, during semantic processing. It must also be noticed that previous studies showing similar activation profiles in sighted and early blind people processing language material do not necessarily indicate that sensorimotor simulations are not recruited during semantic processing. Indeed, there is evidence that occipital regions reorganize for other sensory computations in the absence of vision (e.g., auditory, gustatory). Therefore, a similar pattern of activation over occipital regions may reflect different simulatory mechanisms in the sighted and blinds (Ostarek & Bottini, 2021).

Another approach to test the causality of sensorimotor simulation to semantic processing relies on lesion studies. For instance, some studies on cortical motor lesions show a lack of impairment in action word processing that embodied theories instead would postulate (Arevalo et al., 2012; Weiss et al., 2016), while others suggest action-language specific impairments when the motor system is damaged (Bak & Chandran, 2012). The effect of pathological changes in the motor system such as in Parkinson’s disease can contribute to the investigation of the causality issue: we refer the reader to section 5 of the paper by Ibáñez et al. in this journal issue for an in-depth discussion.

In healthy populations this has been tackled by applying neuromodulation techniques such as transcranial magnetic stimulation (TMS) and transcranial electrical stimulation (tES), and targeting the hand and foot motor areas during the processing of effector-specific action verbs and sentences. Results show that stimulation modulated reaction times and/or cortical excitability, although some inconsistencies remain as for the direction of the modulation in the sense of cortical motor inhibition vs. facilitation (Buccino et al., 2005; Gianelli & Dalla Volta, 2014; Lo Gerfo et al., 2008; Niccolai et al., 2017; Oliveri et al., 2004; Papeo et al., 2009; Pulvermuller et al., 2005; Repetto et al., 2013; Scorolli et al., 2012; Weiss et al., 2016; Willems et al., 2011). Such inconsistencies may stem from diverging stimulation settings (e.g., supra- vs sub-threshold, single-pulse vs. repetitive) and different linguistic tasks involved across different studies. For instance, it has been showed that, whereas TMS of hand motor areas does not affect hand-related word processing in a lexical decision task, a deeper level of processing prompted by semantic judgment task is compromised by TMS in a meaning-specific fashion (Vukovic et al., 2017), as is action-word acquisition (Vukovic & Shtyrov, 2019). Further, performance in a semantic discrimination task seems to affect the effect of tES on priming (Niccolai et al., 2017). Thus, although overall results point to somatotopically organized engagement of cortical motor areas in the understanding of written and spoken action, the issue of causality remains debated and is in need of further studies that should more systematically explore different modalities, stimulation regimes and linguistic contexts.

How are Abstract and Concrete Words Grounded?

Language is a powerful vehicle for the expression of knowledge: by mapping mental representations of objects, actions, and facts of the world onto word meanings, it allows individuals to share thoughts, experiences, and feelings, in order to be understood by others. For example, people can talk about things they can experience directly through their senses, such as dog and pizza, but they can also talk about more abstract entities, such as, intelligence and justice, which constitute around 70% of the words individuals use daily (Bolognesi & Steen, 2018; Recchia & Jones, 2012). These latter concepts pose a problem for theories that ground knowledge in sensorimotor systems (e.g., embodied or grounded cognition theories). Indeed, how can sensorimotor activation systems represent words that do not appear to be grounded in these systems? Within the general aim of this consensus paper, this section addresses this question from various perspectives by examining studies comparing abstract and concrete word processing, in order to provide an overview of current approaches to the possible commonalities and differences in the grounding of these words and to suggest future directions in this strand of research. The conceptual metaphor theory addressed this question by observing that in language, concrete words are often used as a metaphor to talk about abstract concepts (Lakoff, 1980; Pecher, 2018). A body of behavioral data supported this theory, showing that people activate some sort of spatio-motor representations when they talk and think about abstract concetps, consistent with embodied semantics. On the other hand, neuroimaging studies observed mixed results. For instance, when comparing metaphorical sentences including action words and action-related literal sentences, while Aziz-Zadeh et al. (2006) failed to report motor activation for the idiomatic sentences, Boulenger et al. (2009) found this activation. Yet, it is unlikely that all abstract concepts can be grasped thanks to their metaphorical relations with concrete concepts (Borghi & Zarcone, 2016). An alternative idea is that, compared to concrete words, abstract ones have more situation-dependent properties (Wilson-Mendenhall et al., 2011). Providing situational information often facilitates the processing of abstract words (Murphy & Wisniewski, 1989; Schwanenflugel & Shoben, 1983; Wattenmaker & Shoben, 1987), suggesting that situations are important for understanding these types of words.

In the literature, the property that determines whether a word is concrete or abstract has been termed concreteness. By definition, concreteness indicates the degree to which a word refers to an entity that can be perceived through the external senses. This dimension is usually assessed by participants on Likert scales (Brysbaert et al., 2014; Montefinese et al., 2014), in which concrete words lie on one side of the scale, referring to single, bounded, identifiable referents that can be perceived through the senses (Borghi et al., 2017). Abstract words lie on the opposite side of the scale and lack clearly perceivable referents with the affective words more strongly reliant on interoception (i.e., sensations inside the body; Connell et al., 2018; Montefinese et al., 2020). Indeed, compared to concrete words, abstract ones are acquired later and mostly through language and social interaction rather than physical sensorimotor experience (see Borghi et al., 2019; Dove et al., 2020). Concrete words are more imageable (Paivio, 1990) and have greater availability of contextual information (Schwanenflugel et al., 1992). Different organizational principles have been argued to govern semantic representations of concrete and abstract words (Montefinese, 2019). Indeed, concrete words are predominantly organized by similarity in the sensorimotor experience (Montefinese et al., 2015; 2018a), as has been inferred from asking participants to list properties of the concept which a word refers to (Buchanan et al., 2019; Montefinese et al., 2013; Montefinese & Vinson, 2015). Abstract words, in turn, are mostly organized by associative relations, which indicate the extent to which words are bound in the mind (as inferred by a free word association task; Crutch & Warrington, 2005; Montefinese et al., 2018b). It has also been proposed that abstract word representation could be based more on semantic similarity arising through patterns of words’ co-occurrence in linguistic contexts and syntactic information, based on the idea that words with similar meanings are mostly used in similar linguistic contexts (Vigliocco et al., 2013). However, some studies in the literature have questioned the latter claim by showing that lexical co-occurrence-based models either predict the processing of concrete and abstract words similarly (Rotaru et al., 2018) or account better for concrete than abstract words (Hill et al., 2013; Montefinese et al., 2021; see also the next section).

Concrete words can also be inscribed into definite domains, such as natural objects vs. artifacts, plants vs. animals, etc., and they are organized into hierarchical categories (animals/dogs/terriers/), while abstract words are considerably more variable with regard to their semantic content and they cannot be contrasted as a uniform category with concrete words (Borghi et al., 2017; Montefinese et al., 2015; but see Troche et al., 2014). Moreover, participants agree more when they produce properties and associations for concrete words like dog and pizza compared with abstract words like intelligence and justice (De Mornay Davies & Funnell, 2000; Tyler et al., 2002). This could be due to abstract words generally having a greater number of possible meanings (i.e., polysemy or semantic diversity) compared to concrete words (Hoffman et al., 2013). This ontological distinction is reflected in their different processing and representation in the human brain. Indeed, a mounting body of evidence from functional neuroimaging studies supports the idea that the left and right cerebral hemispheres differ in their processing of concrete and abstract words (e.g., Binder et al. 2005; Dhond et al., 2007; Pexman et al. 2007; Sabsevitz et al. 2005). The general consensus from these studies is that two main systems underlie the processing of these types of words, with abstract words relying on the verbal-language system and concrete words relying on the imagery and perceptual systems (Wang et al., 2010) as previously suggested by the seminal work of Paivio, who conceptualized this in his dual coding theory (Paivio, 1990, 1991; see below).

Moreover, behavioral research over several decades has found that concrete words are processed more quickly and accurately than abstract words (for a review, see Huang & Federmeier, 2015). This processing advantage is labeled concreteness effect and has been observed in a variety of tasks. For example, as compared to abstract ones, concrete words are responded to more quickly in lexical decision tasks (Bleasdale, 1987; Kroll & Merves, 1986; but see also Kousta et al., 2011), are easier to encode and retrieve (Romani et al., 2008; Miller & Roodenrys, 2009), are easier to make associations with (de Groot, 1989), and are more thoroughly described in definition tasks (Sadoski et al., 1997). Although it has recently been suggested that some of these effects may be driven by surface word properties and their acquisition backgrounds rather than semantics per se (Kurmakaeva et al., 2021) and some studies have even documented the reverse of concreteness effect when surface properties are matched (Mkrtychian et al, 2021), the evidence in favor of general concreteness word advantage remains ubiquitous.

Two main competing theories have been proposed to explain the concreteness effect. As mentioned above, the dual coding account (Paivio, 1990) claims the existence of two processing systems: a verbal symbolic system responsible for the representation and processing of linguistic information, and an imagery system for the nonverbal information. This theory argues that abstract words are only represented through a verbal code, while concrete words are represented using both a verbal and non-verbal code, resulting in an additive effect and processing advantage for concrete words over abstract words (Paivio, 1990). Thus, similarly to the amodal theories (Mahon & Caramazza, 2008), Paivio‘s theory neglects the grounding of abstract meaning and claims that only a symbolic amodal system plays a role in the processing of abstract concepts. Within the dual coding framework, a hybrid view combining an embodied approach with a distributional one seems promising (Andrews, Frank & Vigliocco, 2014; Montefinese, 2019). Indeed, distributional models based on linguistic data appear to be appropriate for describing abstract concepts (Louwerse, 2011).

In contrast to the dual coding account, the context-availability model (Schwanenflugel, 1992) pays no attention to the special status of the perceptual information, rather it claims that abstract and concrete words are represented in a single symbolic system. This theory assumes that comprehension relies on context supplied by either the preceding discourse or the comprehender’s own semantic knowledge. Concrete words are more closely associated with the relevant contextual knowledge in semantic representation because they have stronger or more extensive connections to this stored knowledge compared with abstract words. Thus, the poorer performance for abstract words is due to the relative unavailability of associated contextual information in semantic representation for these words (Schwanenflugel, 1992). Abstract words may be associated with a wider variety of situations than concrete concepts (Galbraith & Underwood, 1973) given their greater number of meanings, as mentioned above (Hoffman et al., 2013). As a result of greater interference between competing situations, retrieving a single one may be more difficult for an abstract word than for a concrete one.

Unlike laboratory studies where words are presented in isolation, when people process abstract words in the real world, a relevant situation is already in place and this could facilitate the processing of abstract words by resolving the interference between competing situations. Indeed, some studies observed that differences between concrete and abstract words are reduced when abstract words have sufficient contextual support (Schwanenflugel, 1991; 1992; see also the next section). In sum, in both the dual coding and the context availability accounts, concrete semantic representations are posited to be richer than abstract semantic representations. Moreover, they both overlook the contribution of the semantic grounding and embodiment in the organization of abstract representations.

EEG and, in particular, the ERP technique is particularly suitable to study functional differences in the processing of abstract and concrete words due to its high temporal resolution. Thus, ERP studies may unveil the time-course of multiple processes that are summated in behavioral measures (Huang & Federmeier, 2015). The ERP literature on the concreteness effect appears generally consistent across a wide variety of cognitive tasks, such as, imageability ratings, lexical decisions, go-no tasks, congruency and semantic judgments, implicit and explicit memory tasks (e.g., Adorni & Proverbio, 2012; Barber et al., 2013; Kanske & Kotz, 2007; Lee & Federmeier, 2008; Swaab et al., 2002; West & Holcomb, 2000). Overall, ERP studies show an N400 component (a negative-going waveform in centro-parietal electrode sites peaking around 400 ms post-stimulus) generally associated with the processing of meaning and in particular with semantic access (for a comprehensive review, see Kutas & Federmeier, 2011). ERP studies on the concreteness effect showed a larger N400-like component for concrete words compared with the abstract ones generally spanning from 300 to 500 ms after the onset of the target stimulus, often extended to the frontal sites. In accordance with the context availability theory, this pattern of results could be driven by the more availability of contextual information for concrete words. Another interpretation posits that concrete words evoke more activity in semantic representation eliciting a larger N400 (Barber et al., 2013) because of their richer semantic networks (in terms of multimodal features), supporting the claim of a strong grounding in the sensorimotor experience of concrete words. Indeed, in line with the idea that the N400 reflects the level of meaning activation (Molinaro, Conrad, Barber & Carreiras, 2010), the authors proposed that when words are presented out of context, compared to the concrete concepts, the abstract ones would activate superficial connections with their associate words, resulting in a shallower activation process. This is consistent with the fact that when the words are presented with a context (like in the priming studies) the N400 concreteness effect disappears (as discussed in the following section).

A concreteness effect has also been found in ERP amplitudes as early as 150 ms (Mkrtychian et al., 2021) and a at later time of the sustained frontal N700 (typically spanning between 300 and 900 ms), consistent with the dual-coding account, which attributes the concreteness effect to the availability of sensorimotor imagery primarily involved in concrete word processing (Huang & Federmeier, 2015). This latter pattern of results provides once again evidence for a semantic grounding of the concrete words. Holcomb et al. (1999) speak in favor of a context-extended dual coding theory, which integrates (but it also differentiates from) the context availablity and dual coding theories at the neurophysiological level. Upon closer inspection, while the context availability would posit larger context effects for abstract words, the context-extend dual-coding theory would predict similar effects for abstract and concrete concepts within the verbal system. Moreover, it would posit larger contextual effects for concrete than abstract words in the imagery system. This account is supported by many neuroimaging studies (e.g., Bechtold et al., 2022; West & Holcomb, 2000; Binder et al., 2005; Zhang et al., 2006), still generally supporting the idea that the neural processing of abstract and concrete words is different.

What Can Semantic Priming Tell Us About Embodied Word Representations?

In real life, we rarely process words in isolation. Thus, to draw ecologically valid conclusions about the mechanisms of embodied language processing in the human brain, it is important to look at how word processing varies according to the (linguistic) context in which it occurs. One powerful tool to embed words in context and still disentangle mechanisms involved in word vs. context processing is semantic priming. In semantic priming, a semantically congruent prime facilitates the processing of the following target word, which leads to shorter reaction times or higher accuracy, with the opposite pattern for incongruent prime-target combinations (Meyer & Schvaneveldt, 1971; for a review see Neely, 1991). Possible neural mechanisms underlying priming effects include forward- and backward-directed mechanisms. Forward-directed mechanisms have been discussed to include (automatic) spreading activation in the semantic network (Collins & Loftus, 1975; Kiefer, 2002) and predictions (Delaney-Busch et al., 2019; Lau et al., 2016) or controlled expectancy generation (Aurnhammer et al., 2021; Frade et al., 2022). Backward-directed mechanisms include integration and re-evaluation/prediction-error adaptation (Jack et al., 2019; Steinhauer et al., 2017). These processes can act within the semantic network connecting the prime and target word as well as across domains. Thus, measuring behavioral or neural consequences of semantic and cross-domain priming allows inferences about the organizational principles of embodied word representations.

To find out what semantic priming can tell us about embodied word representations, we focus on two lines of research in the following. The first line directly takes up the differences between concrete and abstract words presented in the section above and focuses on what concrete vs. abstract word priming effects driven by similarity- and association based relations can reveal about the organizational principles of lexico-semantic word representations. The second line focuses on what cross-domain priming within the abstract domain of numerical cognition can reveal about embodied perceptual information in abstract word representations. Finally, we will provide future directions on how to exploit the potential of semantic priming paradigms in embodied and situated language processing research.

What Can Embodied L2 Learning Teach us About the Role of Embodiment in Language Representation?

Understanding how we first associate concepts to words is crucial for grasping how we represent language. In line with the Hebbian theory of associative learning, the “correlational learning principle” claims that the co-occurrence of action-perception and meaning results in the common firing of neurons, forming “embodied referential semantic circuits” to support meaning representation (Pulvermüller, 2013). Indeed, studies on verbal memory in the native language (L1) have shown that self-performed actions, associated to word labels during encoding, boost memory performance and supports word learning, a phenomenon called enactment effect (Engelkamp & Zimmer, 1985). More recently, learning language with self-performed or self-generated action that is directly linked to the learned content has been referred to as “embodied learning”. In this sense, studies on second language learning (L2) can provide relevant insights concerning the role of embodiment in language processing. Indeed, neurocognitive studies have become increasingly interested in scrutinizing motor-semantic interactions from initial word encoding in L2 to better understand the role that embodiment may play in language learning (i.e., facilitation). As we will discuss in the following subsections, drawing links between associative language learning and sensorimotor processes has proven both fruitful and extremely complex, pointing to a promising avenue in studies examining embodied processes.

How Does Object Modality Affect Associative Word Learning and Modulate the N400?

Humans experience the world through sensory input, and language allows us to communicate these experiences to one another, including naming and describing visual, auditory, olfactory, haptic, and gustatory objects and events. Recent research has provided insights into the distribution of nouns pertaining to the allocation of perceptual modalities in vocabularies across several languages (e.g., Chedid et al., 2019; Chen et al., 2019; Lynott et al., 2020; Miklashevsky, 2018; Morucci et al., 2019; Speed & Majid, 2017; Vergallito et al., 2020; Winter et al., 2018). However, research on word learning typically focuses on the acquisition of and mapping of words onto visual objects (e.g., Friedrich & Friederici, 2008, 2011; Horst & Samuelson, 2008; Junge et al., 2012; Smith & Yu, 2008; Taxitari et al., 2019; Werker et al., 1998). It is known that sensory modality not only impacts the outcome of learning, but also the parameters of learning, for example directionality of preference (novelty effects vs. familiarity effects) and age (Emberson et al., 2019; Thiessen, 2010); yet, this has not often been considered in the context of language acquisition. Thus, differences between learning words for visual objects and other object modalities, such as auditory objects, are not well known. An understanding of how word learning takes place for other modalities is important, as perception is the key factor of embodied and embedded cognition within a situated cognition framework (cf. Venter, 2021). Recent research in infants has suggested that 10-month-olds are able to map labels onto auditory objects (i.e., environmental sounds) in a similar way to mapping labels onto visual objects (Cosper et al., 2020). Moreover, recent research has also provided evidence that not only the modality of the object (visual vs. auditory) but also the temporal synchrony of stimulus presentation can also have an effect on learning in both ERP and behavioral measures (Cosper et al., 2022).

The sensory modality of processing has been known to have an effect on memory. This can be seen specifically in recognition memory, where, for example, the recognition for visual objects is found to be superior to that of auditory objects (Cohen et al., 2009, 2011; Gloede & Gregg, 2019). Furthermore, short-term memory and delayed recognition in the visual and tactile modalities has also been shown to be superior to that in the auditory modality (Bigelow & Poremba, 2014). However, short-term memory differences seem to diminish and memory recall becomes more similar when the complexity of stimuli in the auditory and visual modalities are closely matched (Visscher et al., 2007). Thiessen (2010) identified two constraints to modality effects on word learning in adults and infants: the developmental constraint, which refers to differences in auditory stimulus processing between infants and adults process the auditory stimuli differently, and the stimulus constraint, implying that characteristics of word-object stimuli are processed differently according to modality.

In order to acquire the meaning of a word, the object and its label must first be mapped onto one another. This relationship can be formed in two basic, yet different, ways, in which the outcomes are not necessarily mutually exclusive: by means of referential relationships, such as hypothesis testing (cf. Xu & Tenenbaum, 2007) or by means of associative relationships (e.g., Bergelson & Aslin, 2017; Bergelson & Swingley, 2012; Friedrich & Friederici, 2011; Sloutsky et al., 2017). In the case of word learning for auditory objects, the cognitive mechanisms of maintaining auditory short-term memory are important considerations for the outcome of learning. Baddeley (2012) gives a review of the phonological loop, an auditory working memory maintenance system reliant on vocal or subvocal rehearsal. The phonological loop is said to not only be utilized for auditory-verbal stimuli, but also for auditory-nonverbal stimuli (Baddeley, 2012). However, more recent research has provided an alternative system of working memory maintenance for auditory-nonverbal stimuli, namely a cognitive mechanism similar to visual imagery – auditory imagery – which details that auditory-nonverbal information may be maintained in working memory by imaging a sound (Soemer & Saito, 2015). Albeit there are differences in the two mechanisms underlying working memory in the auditory modality, it could be that both are necessary in auditory word learning, as both auditory-verbal and auditory-nonverbal information is present in such learning situations in the form of spoken words and auditory objects, for example, environmental sounds. This notion has been seen in adult learners, but needs to be further explored and excplicitly manipulated in an experimental setting in order to fully understand how the pholological loop and auditory imagery are affected by object modality in word learning (cf. Cosper et al., 2022).

The ERP method can be applied in order to provide insights into the neural underpinning of learning, along with additional behavioral measures such as accuracy and reaction times obtained through an active learning paradigm (McLaughlin et al., 2004). We already mentioned N400, as one of the most important components in linguistic ERP research; it is not surprising that it has also been used to address the learning processes. In addition to the classical sentential contexts, the N400 has also been used to measure word learning in isolation (for reviews, see Junge et al., 2021; Kutas & Federmeier, 2000, 2011). In addition to spoken or written words, the N400 component can also be used to measure processing of non-linguistic material, such as tones, music, and environmental sounds (Cummings et al., 2006; Koelsch et al., 2004; van Petten & Rheinfelder, 1995), indicating that the N400 can be used as a measure of violated expectation with both auditory-verbal and auditory-nonverbal stimuli. As such, the N400 component can be used to measure learning in associative word learning paradigms during and after learning with both auditory and visual objects paired with spoken pseudowords.

Recent empirical evidence has been provided that infants are able to map words onto auditory objects (i.e., environmental sounds) in a similar way as they do for visual objects (Cosper et al., 2020); however, first evidence provides insight in that auditory associative word learning is less effective than visual associative word learning (Cosper et al., 2022). Despite these findings, there is still a gap in the literature on how the full spectrum of perceptual modality features affects word learning and emodied and situated cognition of language processing. Nonetheless, one can speculate about the possibility of object modality affecting associative word learning and, in turn, modulating the N400 in adults. The functional interpretation of the N400 effect is generally described as either a process of spreading activation (e.g., Holcomb, 1988; Kiefer, 2002; Lau et al., 2008) or semantic integration (e.g., Bentin et al., 1993; Kutas & Federmeier, 2011). However, as mentioned above, there are other functional interpretations of the N400 effect, which include factors such as predictability (semantic-level), plausibility (sentence-level), and similarity (low-level semantic relationship, based on co-occurrence; Nieuwland et al., 2020). More recent research also shows that the latency of the N400 (or N500, cf. Schöne et al., 2018) is sensitive to tension and stress in processing personally relevant stimuli (Schöne et al., 2018; Carretie et al., 2005). As such, factors beyond semantic integration or spreading activation can affect the latency of the N400 effect; thus, it is possible that object modality also can affect the latency of the N400 effect (cf. Cosper, 2020; Cosper et al., 2022). It is also important to note that the topological distribution of the N400 can also differ across studies, which can be influenced by factors such as stimuli-specific processing demands, vocabulary, and age (for a review in infants and young children, see Junge et al. 2021); however, this section focuses on and highlights the effects on latency. Based on these alternative functional interpretations of the N400 component, we can consider how object modality may also reflect functional differences in the processing, learning, and mapping of labels onto objects of various modalities.

In order to consider object modality in terms of functional differences pertaining to associative word learning, one must first consider how modality affects processing, memory, and word acquisition both in isolation and taken together. Importantly, the N400 component itself is an effective measurement of processing and learning with non-linguistic auditory stimuli (Cummings et al., 2006; Koelsch et al., 2004; van Petten & Rheinfelder, 1995). It is further well known that the N400 component can also measure violations of (semantic) expectation in line drawings (cf. Kutas & Federmeier, 2000). Thus, the N400 component itself is highly flexible and can be used to measure learning by means of violated (lexico-)semantic expectation in at least the visual and the auditory-verbal as well as auditory-nonverbal modalities.

As briefly presented above, it is known that object modality affects recognition memory, short-term memory, delayed recognition, and memory recall (cf. Bigelow & Poremba, 2014; Cohen et al., 2009, 2011; Gloede & Gregg, 2019; Visscher et al., 2007) as well as statistical learning, extracting regularities from repeated exposure to information input over time, in both infancy and adulthood (e.g., Emberson et al., 2019; Saffran, 2002; Saffran et al., 1996, 1999). Another recent study (Miller et al., 2018) provided evidence that, following a series of training sessions with implicit verbal-tactile association learning, participants exhibited enhanced tactile perception to consistently labeled verbal-tactile pairs compared to those who were trained on inconsistently labeled pairs, thus suggesting a causal relationship between language and perception (see also Schmidt et al., 2019 and the L2 section above). In sum, associative word learning is affected by object modality (visual vs. auditory) and, given the latency costs in processing, recognizing, and recalling visual versus auditory stimuli, the latency of the N400 component in auditory associative word learning may be functionally affected by the modality of the object being labeled.

What Can Virtual Reality Bring to Embodied Language Processing and Learning Studies?

When it comes to how language is processed and learned, theories of embodied and situated cognition give a great deal of importance to physical contexts. This poses a major challenge for neurocognitive studies in these fields, as it calls for more multimodal and close-to-life experimental protocols that are more ecologically valid while still allowing for strict experimental control (Tromp et al., 2018; Peeters, 2019). In this context, VR approaches may provide an important tool to achieve this balance. VR has been said to eliminate the spatial divide between stimulus and participant (Peeters, 2019). Clearly relevant for embodied language processing and learning research, VR provides participants with more ecologically valid, interactive and immersive environments, thought to better engage the sensorimotor system and elicit real life responses (Bohil et al., 2011). Furthermore, while language studies are generally constrained to focus on a single modality (e.g., speech), VR allows for the observation of how different modalities (e.g., speech, body movements, facial expression) interact with each other – as is the case in real-life communication – in rich, closer-to-life environments (Peeters, 2019). Finally, immersive VR protocols allow participants to engage in semi-natural actions, which should lead to results that can generalize to real life (Peeters, 2019).

So far, very few studies have combined VR and cortical measures to investigate embodied language processing. Tromp et al. (2018) validated the use of VR to investigate language processing by measuring EEG while participants wore a head-mounted VR display, immersed in a virtual restaurant. As they listened to a sentence (“I just ordered this salmon”), participants saw a virtual object that either matched (salmon) or mismatched (pasta) the object in the sentence. As expected, a match-mismatch N400 effect emerged when items were incorrectly labeled orally, compared to correctly labeled items. This was considered a proof of concept for combining EEG and immersive VR to observe neurocognitive language processing. Within an embodied semantics perspective, Zappa et al. (2019) measured cortical motor activation during action verb processing in a Cave automatic virtual environment (an immersive VR environment that surrounds users while allowing them to see their own body). The study focused on changes in the mu (8–13 Hz) and beta (20–30 Hz) frequency bands, associated with motor activity, as participants performed a Go-Nogo task. Participants heard action verbs and, for Go trials, performed a corresponding action on a virtual object. Mu and beta band suppression was found for both Go and No-Go trials. Importantly, mu suppression emerged 400–500 ms after action word onset, associated with lexical-semantic processing, and more so for Go trials, indicating an interaction between motor and linguistic processes. Whereas L1 studies have used VR to examine language processing, a few experiments have taken advantage of this technology to explore L2 learning. In a longitudinal fMRI study, Legault et al. (2019) taught L2 words to novice learners using the Second Life gaming platform virtual environment, compared to a control group that learned via picture-word association. For both groups, results revealed increased cortical thickness and gray matter volume in regions implicated in a language control network after training. Furthermore, within this network, L2 training in the picture-word association group led to greater cortical thickness in the right inferior frontal gyrus, whereas training performance in the VR group was positively correlated with cortical thickness in the right inferior parietal lobule (associated with superior L2 proficiency, Mechelli et al., 2004). Also, for the VR group, accuracy in the delayed retention post-training was positively correlated with cortical thickness in the right supramarginal gyrus. These results indicate that training in virtual environments leads to rapid cortical changes that differ from those found after picture-word association learning. Also, VR learning is thought to have led to a stronger engagement of the inferior parietal lobule in immersive and interactive L2 learning, as it stimulated embodied processes (Li et al., 2020).

Using a different approach, in a TMS study Vukovic and Shtyrov (2019) examined embodied semantics in a VR setting by interfering with participants’ M1 during novel word learning in order to test whether this would affect verb encoding. An interactive VR computer game was used to teach participants novel labels for object nouns and action verbs as they manipulated virtual objects. Theta-burst TMS was applied to participants’ M1 prior to learning and, as predicted, they were less successful at encoding novel verbs compared to nouns when the hand area of the left M1 was stimulated. Applying theta-burst TMS to the M1 was thought to prevent a motor trace from forming for verb labels, suggesting that motor cortex activity was involved in the early stages of word encoding. Furthermore, the same VR-TMS design combined with diffusion kurtosis imaging (DKI) showed a range of microstructural changes taking place in the brain over the short learning session (Vukovic et al., 2021). Generally speaking, the above-described language processing and learning studies illustrate that VR allows for the manipulation of naturalistic movement and environments and can be combined with cortical measures to successfully examine embodied semantics.

A completely new field of research is concerned with the investigation of the role of the virtual action (VA) on language learning and comprehension. A VA is an action performed within a virtual environment, exploiting VR technology. Experiencing a virtual world immersively (i.e., by means of a head-mounted display or a Cave automatic virtual environment) gives users a subjective feeling of agency. Specifically, immersive VR allows us to represent our movements from the first-person perspective and to feel like agents of the actions we perform. Therefore, VR users can have the subjective feeling of performing a VA either by seeing their virtual body parts performing an action (e.g., the virtual hands grasping an object) or by perceiving changes in the optical flow consistent with that action (e.g., users can feel as if they are virtually walking when presented with a coherent change in the optical flow of the virtual environment). It should be noted that a VA can have a real counterpart, i.e a real action performed by the individual, which either matches the virtual one or not (the user can point in a given direction with her real hand and, at the same time, see her virtual hand perform the same action – match; or the user can press a button with her real hand and see the virtual hand pointing to something – mismatch). In some cases, the VA can also have no real counterparts (e.g., the user is still but sees herself walking into the virtual environment). A few studies have begun to shed light on the cortical underpinnings of VA (Adamovich et al., 2009; Holper et al., 2010). According to their findings, the observation, imagery, and execution of actions with real-time virtual feedback share common neural substrates located within the observation-execution network. Carrieri et al. (2016) investigated the cortical activity during a demanding hand controlled task in VR, and observed a ventrolateral prefrontal cortex involvement, compatible with the recruitment of attention resources needed to accomplish the task. A VA performed with the legs (virtual walk) was investigated by Wagner et al. (2014), who manipulated the visual feedback provided within the virtual environment. They found that during the virtual walk (with coherent visual feedback in the 1^st and 3^rd person point of view) premotor and parietal areas showed increased activity compared to the conditions in which the visual feedback was unrelated to the motor task, or in which it consisted of a mirror-image of a VR avatar. Taken together, these results clearly indicate that VA can modulate the cortical motor system.

The impact of VA on language processing has been investigated by a few studies using basic virtual environments (Repetto, Cipresso, et al., 2015; Repetto, Colombo, et al., 2015), which demonstrated that a VA performed with a specific body part (e.g., legs) can facilitate semantic comprehension of verbs describing actions performed with the same effector (Repetto, Cipresso, et al., 2015). Similarly, learning L2 words could be improved by performing a VA with the effector matching that described by the action verb to be learned (Repetto et al., 2015).

Conclusion

According to situated and embodied theories (including embodied, embedded, extended, enacted, and grounded cognition approaches), language representation is intrinsically linked to our interactions with the physical world. The initial rivalry between embodied and amodal theories has given way to a more flexible approach that aims to determine when and how perceptuomotor mechanisms are involved in language processes, alongside modality-independent processes. This consensus paper is not an exhaustive review of embodiment studies but rather addressed carefully selected questions by presenting seminal research as well as recent methodological developments that can point to future directions in the research field of embodied and situated language processing.

In the area of language processing, we presented evidence based predominantly on ERPs/ERFs as well as oscillatory markers that, at least in some contexts, suggests that motor and perceptual information comprised in language representation rely on brain resources partially overlapping with motor and perceptual experience. We are currently facing the challenge of the functional interpretation of these markers. Future research investigating, e.g., the laminar profile of the underlying neural resources seems promising to examine how the same resources can subserve both the physical experience and semantic processing. Further, the comparison between abstract and concrete word processing was shown to unveil fundamental differences in their grounding. A crucial next step is to systematically explore task-dependent, situated grounding along the concreteness continuum. We showed that semantic and cross-domain relations lead to differential priming effects, which can reveal organizational principles interconnecting the multiple dimensions of embodied word representations. Future research should focus on individual and situational differences in these effects as well as on disentangling whether cross-domain priming relies on an overlap in general cognitive mechanisms vs. specific representational content. In the area of language learning, we showed that word acquisition based on gestures and other motor actions reveals a supporting and at least partially causal role of embodiment in acquiring language representations. Here, future research might focus on greater body engagement and manipulation of the environment via VR to enhance ecological validity as well as target the role of perspective-taking. We provided evidence that object modality affects the N400 in adult word learning in a situated manner. The generalizability across perceptual modalities and culturally diverse societies is an important future step. Finally, we argued for the value of VR and VA as tools to support and modulate language learning and rehabilitation, providing highly controlled, close-to-life set-ups supporting language (re-)acquisition in previously inaccessible situations.

The puzzle pieces presented above point to common future directions in investigating the brain signatures of embodied and situated language processes. Our research field has greatly benefitted from fundamental research testing well-defined hypotheses by following a reductionist approach to multimodality (e.g., motor vs. visual information in learning/processing language entities from distinct categories) or semantic multidimensionality (e.g., the concrete vs. abstract distinction). We value this seminal research, as it formed and informed a dense theoretical network, which we can now use as a launch pad to aim higher and achieve external validity based on more complex research designs with more sophisticated as well as more ecologically valid methods. Importantly, new acquisition and analysis methods based on ever-growing computing capacities now call for acknowledging the multimodality, multidimensionality, flexibility and idiosyncrasy in embodied and situated language processes. These dimensions are determinant in probing embodied and especially situated language processes in the future, as they can potentially explain many of the discrepant findings of studies following a reductionist approach.

The red thread through the sections presented above is a consensus on a basic understanding of embodied, situated language processes: these do not require that (primary) sensorimotor areas be automatically and causally involved independently from stages of language learning, representation, and processing or individuals or tasks and contexts (see also Barsalou, 2020). In contrast, brain signatures of embodied and situated language processes are flexible, as their evolutionary rationale with the primary goal to allow an efficient online processing of language calls for this flexibility in the face of our ever-changing environment. The complexity and versatility of situated embodied language processes thus cannot be reduced to a dyadic (on/off) character as suggested by the concept of all-or-nothing causality and automaticity. The replication crisis (Kellmeyer, 2017; Laws, 2016; Zwaan et al., 2017) luckily forced research in this field to tackle this problem by running large-scale studies investigating embodied phenomena in multiple different tasks (e.g., ManyBabies Consortium, 2020; Morey et al., 2021; Pavlov et al., 2021), by taking into account cultural diversity (Bettinsoli et al., 2021), and providing research guidelines to make ERP research more consistent in design and reporting (e.g., Paul et al., 2021; Šoškić et al., 2021; Styles et al., 2021).

With this development, research in our field can now move from a focus on internal validity, which favored reducing the dimensions of our investigations, to a focus on external validity, which now begins to favor more true-to-life, complex research designs. In this sense, future research can examine multidimensionality and multimodality in language processes rather than breaking them down to, for example, dichotomous formats. We can move from investigating isolated semantics to the broad variety of mechanisms and interactions involved in contextual language processes. Furthermore, we can use VR to enhance external validity by incorporating more true-to-life movements and perceptual experience in a still controlled laboratory setting. Instead of asking whether language processing is embodied, we can ask how and under what circumstances perceptuomotor brain areas support conceptual processing. In this regard, a special focus on the functional interpretation of long-standing markers of embodied language processes like different ERP/ERF components, neural oscillations and their time course as well as neuromodulation methods that can show causal brain-behavior relationships will accompany us throughout the next decades of research on the brain signatures of embodied and situated language processing. Overall, this consensus paper delivers a glance at the state of the art regarding different factettes of the research around embodied and situated language processes. Our hope is that it will help other researchers to identify where their research stands in relation to what has been examined and how it has been examined. Specifically, we hope that theoretical and practical implications from some of the fields we have discussed (e.g., priming studies, VR studies, etc.) could inspire other fields within embodied & situated language processes research.

Author Notes

Correspondence regarding the content of specific sections can be addressed to the following authors (in the case of multiple authors in a section, authors listed in alphabetical order):

Ethics and Consent

As this paper does not present original empirical data, ethical approval and/or consent was not required.

Funding information

The work reported here was supported by the Italian Ministry of Health under grant number GR-2019-12371166 to MM. The Deutsche Forschungsgemeinschaft 574 (SFB991) financed the work of VN. AM acknowledges support from the Russian Foundation for Basic Research Grant (project no. 19-313-51023) awarded to the National Research University Higher School of Economics. PM received support from “la Caixa” Foundation (ID 100010434) through the fellowship LCF/BQ/IN17/11620019, and the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement no. 713673. AZ’s research was supported by grants ANR-16-CONV-0002 (ILCB), ANR-11-LABX-0036 (BLRI) and the Excellence Initiative of Aix-Marseille University (A*MIDEX).

Competing Interests

The authors have no competing interests to declare.

Author Contributions

All authors contributed to conception of ideas, writing and editing of the manuscript.

Laura Bechtold, Samuel H. Cosper, Anastasia Malyshevskaya, Maria Montefinese, Piermatteo Morucci, Valentina Niccolai, Claudia Repetto and Ana Zappa are shared first authors.