1. Introduction
In cognitive science, the traditional view is that cognitive processing is modular and that high-level thinking (such as categorization, reasoning, and decision-making) involves symbolic computations that are not directly linked to our perception and action systems (Fodor, Reference Fodor1983; Mahon & Caramazza, Reference Mahon and Caramazza2008).Footnote 1 Within this framework, the cognitive and language systems are also believed to be independent of each other and guided by universal determinants (Chomsky, Reference Chomsky1977; Gleitman et al., Reference Gleitman, January, Nappa and Trueswell2007; Papafragou et al., Reference Papafragou, Hulbert and Trueswell2008; Pinker, Reference Pinker1989; Tomasello, Reference Tomasello2003).
Over the last two decades, an opposing, situated view has gained scientific support, arguing that cognitive processing is better understood not as a set of isolated computations that take place solely inside the brain, but rather as emergent properties that result from the constant interaction of the brain with the body (sensorimotor system) and the environment. For such views, see, for example, the embodied accounts of cognition proposed by Barsalou (Reference Barsalou2008) and others (e.g., Gallese & Lakoff, Reference Gallese and Lakoff2005; Willems & Casasanto, Reference Willems and Casasanto2011; Willems & Hagoort, Reference Willems and Hagoort2007); the action perception theory proposed by Pulvermüller (Reference Pulvermüller2013) (see also Kiefer & Pulvermüller, Reference Kiefer and Pulvermüller2012; Pulvermüller, Reference Pulvermüller2018; Pulvermüller & Fadiga, Reference Pulvermüller and Fadiga2010); and the complex and dynamic systems theory by De Bot (Reference De Bot, Ortega and Han2017). In this line of work, various high-level cognitive processes, including language processing, have been found to actively interact with both perceptual and motor systems (e.g., for visual perception–language interactions, see Anderson et al., Reference Anderson, Chiu, Huette and Spivey2011; Lupyan & Spivey, Reference Lupyan and Spivey2010; Richardson & Matlock, Reference Richardson and Matlock2007; for motor action–language interactions, see Pulvermüller et al., Reference Pulvermüller, Hauk, Nikulin and Ilmoniemi2005; Spivey, Reference Spivey2007; Wispinski et al., Reference Wispinski, Gallivan and Chapman2020; Zgonnikov et al., Reference Zgonnikov, Aleni, Piiroinen, O’Hora and di Bernardo2017; and for motor action–visual perception interactions, see Tucker & Ellis, Reference Tucker and Ellis1998; Richardson et al., Reference Richardson, Spivey and Cheung2001).
With respect to the interaction of cognition with the environment, more specifically with the linguistic information in the environment, a more relativist approach holds that human cognition may be additionally shaped by language-specific factors (Boroditsky, Reference Boroditsky2001; Bowerman & Levinson, Reference Bowerman and Levinson2001; Choi, Reference Choi2006; Gentner & Goldin-Meadow, Reference Gentner and Goldin-Meadow2003; Hickmann, Reference Hickmann, Hickmann and Robert2006; Lucy, Reference Lucy1992; Whorf, Reference Whorf and Carroll1956, among others). In this context, recent psycholinguistic research has witnessed a growing interest in the language–thought interface, with particular attention to the possible impact of language-specific properties on our cognitive and even perceptual and action mechanisms of processing (Gibson et al., Reference Gibson, Futrell, Jara-Ettinger, Mahowald, Bergen, Ratnasingam, Gibson, Piantadosi and Conway2017; Goller et al., Reference Goller, Choi, Hong and Ansorge2020; Lupyan et al., Reference Lupyan, Abdel Rahman, Boroditsky and Clark2020; Pulvermüller, Reference Pulvermüller2018; Yun & Choi, Reference Yun and Choi2018).
Although most researchers (mostly from the domain of psychology and neurosciences) ‘do not find plausible the idea that the language system is encapsulated’ (Fedorenko & Varley, Reference Fedorenko and Varley2016, p. 16) and rather suggest that language and thought are two distinct and independent systems (e.g., Monti et al., Reference Monti, Parsons and Osherson2012; Papafragou & Selimis, Reference Papafragou and Selimis2010; Varley et al., Reference Varley, Klessinger, Romanowski and Siegal2005), some recent studies in cognitive science and neuroscience tend to admit that language representations might be used in support of reasoning, across a range of domains, particularly under conditions of high cognitive load. More specifically, the role of language has been recognized as important in non-verbal thinking, for example, for the development of certain abilities in understanding others’ mental states (e.g., de Villiers & de Villiers, Reference De Villiers, De Villiers, Mitchell and Riggs2000), for the storage and manipulation of important quantities of information (e.g., Deldar et al., Reference Deldar, Gevers-Montoro, Khatibi and Ghazi-Saidi2021), or for complex problem-solving (e.g., Baldo et al., Reference Baldo, Dronkers, Wilkins, Ludy, Raskin and Kim2005). In other words, in this line of research, language is not considered as fundamental for thinking but rather as a system playing an accessory role, especially when the task at hand is rather demanding, that of a facilitator. It has been shown, for example, that thought (e.g., arithmetic processing, inhibition, theory of mind, music processing, and spatial navigation) is possible without language. For instance, individuals with aphasia, who have almost no or partially impaired ability to understand or produce language, are able to add, subtract, and solve logic problems, think about another person’s thoughts, appreciate music, and successfully navigate and explore their environments (e.g., Soroli, Reference Soroli2018; Willems et al., Reference Willems, Benn, Hagoort, Toni and Varley2011). But is thought limited to these functions? What about complex reasoning such as event recognition, analogical thinking, and decision-making?
The focus of this paper is on spatial thinking and reasoning and on the role language plays (central or accessory) during motion event perception and recognition, attention allocation to different spatial components, spatial encoding, categorization, and decision-making.
Space provides a rich and experimentally tractable domain to investigate language–thought relations of this type (Boroditsky, Reference Boroditsky2001; Levinson, Reference Levinson, Bloom, Peterson, Nadel and Garrett1996) because it is fundamental to human existence while also characterized by considerable cross-linguistic variability (Talmy, Reference Talmy and Shopen1985). With respect to the expression of motion events, this variability includes (but is not limited to) asymmetries across and within languages in terms of (a) types of semantic information that are preferentially encoded (semantic focus) across systems, such as Path and Manner (Jackendoff, Reference Jackendoff1990; Levin & Rappaport Hovav, Reference Levin, Rappaport Hovav and Roca1992) and Source and Goal (Kopecka & Vuillermet, Reference Kopecka and Vuillermet2021); (b) types of lexical and grammatical encoding patterns (locus/distribution of components) (Matsumoto, Reference Matsumoto and Chiba2003; Talmy, Reference Talmy2000); and (c) density, frequency, and complexity (utterance architecture) of the encoded information (Hickmann et al., Reference Hickmann, Engemann, Soroli, Hendriks, Vincent and Ibarretxe-Antuñano2017; Soroli & Verkerk, Reference Soroli and Verkerk2017), which reflect differences in the relative salience of spatial components and variation in the potential combinatorial assemblies a language offers (Ibarretxe-Antuñano, Reference Ibarretxe-Antuñano, Guo, Lieven, Budwig, Ervin-Tripp, Nakamura and Özçalışkan2009; Slobin, Reference Slobin, Hickmann and Robert2006).
Some studies suggest that such linguistic asymmetries do not affect underlying on-line processing (e.g., Gennari et al., Reference Gennari, Sloman, Malt and Fitch2002; Munnich et al., Reference Munnich, Landau and Dosher2001; Papafragou et al., Reference Papafragou, Hulbert and Trueswell2008), while others argue that perceptual and cognitive mechanisms are fine-tuned by language (e.g., Athanasopoulos & Bylund, Reference Athanasopoulos and Bylund2013; Boroditsky, Reference Boroditsky, Spivey, McRae and Joanisse2012; Choi et al., Reference Choi, Goller, Hong, Ansorge and Yun2018; Goller et al., Reference Goller, Lee, Ansorge and Choi2017; Levinson, Reference Levinson2003; Majid et al., Reference Majid, Bowerman, Kita, Haun and Levinson2004). The emerging view is that our perceptual and cognitive systems are partly adjustable depending on specific contexts, but the precise nature and role of factors contributing to activate language effects are still not well understood.
The aim of this study is to determine whether specific typological differences affect visual on-line event processing in relation to specific features of motion events and the extent to which speakers of different languages may attend to different aspects of events while making non-verbal similarity judgments about them and while integrating them into linguistic structures. After a brief review of previous relevant research (Section 1.1), a list of factors that may influence the degree to which language-specific properties constrain verbal and non-verbal behavior is discussed (Section 1.2). Several hypotheses about the potential relationship between verbal and non-verbal behavior are also formulated, with a special focus on encoding patterns, attention allocation, and non-linguistic processing (Section 1.3). The rationale of the method used and the results of a production task and two similarity judgment experiments that tested these hypotheses are presented in Sections 2 and 3, respectively. These sections are followed by a discussion and a conclusion (Sections 4 and 5, respectively) that raise broader issues about the language–thought interface and highlight the contribution of the present study to dynamic and multidimensional models that take into account cognitive, perceptual, and linguistic interactions.
1.1. Linguistic and non-linguistic representations of motion across languages
Although a common set of semantic components of motion can be expressed in most languages, such as Manner (e.g., to jump, to crawl) and Path (e.g., up, into, across), languages provide speakers with a limited number of linguistic means to encode these aspects, acting as ‘filters’ that lead speakers to focus on particular features of scenes and sub-events in their verbalizations and organize them in very different ways (Slobin, Reference Slobin1987). According to Slobin, such differences depend on the subjective component of motion, namely the Manner of motion, and its relative salience from one language to the other (see, i.e., the Manner cline proposed by Slobin, Reference Slobin, Hickmann and Robert2006). In contrast, according to Talmy (Reference Talmy2000), such variation stems from differences in the objective aspects of motion, namely the expression of Path.
According to Talmy’s lexicalization framework (LF) (1985), the languages of the world offer different form-to-meaning mappings to their speakers for the expression of the core spatial component: the Path. For instance, based on the semantics of motion verbs, Talmy makes the distinction between so-called satellite-framed languages, such as English, which privilege the lexicalization of Manner, expressed in the main verb, leaving Path in satellitesFootnote 2 (1), and verb-framed languages, such as French, which highlight the Path of motion instead and leave Manner peripheral (2a) or unexpressed (2b).
Later, Talmy focused on the way a complex event is integrated into a clause and formulated his event integration framework (EF) (1991). More specifically, to fully and compactly describe a voluntary motion event (Figure 1), the speakers need to integrate into their description two events: (a) an event in which the figure is performing a motion (a displacement, such as the one depicted here: moving from inside to outside) and (b) an event in which the figure is moving in a certain Manner and which encodes the co-event (here: walking ). On the two events, the first (the motion event) plays a primary role in the event complex. According to Talmy (Reference Talmy and Hampe2005), this motion event describes the central relationship between the involved figure and the ground (a special configuration that changes during the displacement) and thus is to be considered as the framing event with a core schema that encodes the Path traced by the moving figure. In the example described above (Figure 1), the ‘walking’ event is the co-event that holds a particular supplementary relation to the framing event and describes a relation of a specific Manner of displacement.
Figure 1. Example of a motion event video.
The EF is different from the LF: The EF focuses on the constituent that encodes the core event schema, the Path, and how this is related to the co-event – what is called in this paper: the Architecture-based framework that is interested in the relationship between the type of the described events and the constructions used to package them (utterance architecture); the LF focuses on the specific spatial components of motion (e.g., Path, Manner, Cause), more specifically whether these components are lexicalized or not – what is called in this paper: the focus–locus dimension that is interested in the kind of spatial component(s) encoded (focus analysis) and the specific morphosyntactic units (loci) used to express them (locus analysis).
From the EF point of view, in a satellite-framed language such as English, speakers integrate into one syntactically compact and semantically dense clause both the co-event (Manner) expressed in the verb and the framing event (Path) expressed in extra-verbal elements, in satellites such as particles (e.g., out), as well as in other devices (e.g., prepositions such as into). In contrast, in verb-framed languages, such as French, speakers tend to adopt a distributed pattern in which information about the framing event (Path) is encoded in the verb, but the co-event is left in the periphery, expressed with extra-verbal elements (e.g., adverbials), distributed in other clauses (e.g., gerunds, coordinated/juxtaposed propositions), or completely omitted, as illustrated in (2a) and (2b), respectively.Footnote 3 Such cross-linguistic variation in this filtering process raises questions about the relative impact of language-specific factors on low-level mechanisms contributing to motion event construal and leads to (at least) two main questions: Does this variability mean that people attend to things differently when viewing the same events? Do they focus on different components/different sub-events? If so, what is the psychological reality of these different lexicalization/event integration patterns?
1.2. Weight of the language factor in relation to scene, task, and event types
The relationship between visual processing and verbal planning is still not fully understood mainly because non-linguistic event representations are hard to access and specify (cf. Bock et al., Reference Bock, Irwin, Davidson, Henderson and Ferreira2004; Jackendoff, Reference Jackendoff1996). Most studies reporting language effects on conceptualizationFootnote 4 (see also Levelt, Reference Levelt1989, for a tripartite model of the speaking process) are based on analyses of production data that show different verbal behaviors across languages, suggesting that the particular linguistic resources of speakers’ native language invite different event conceptualization and encodings. It is only recently that researchers have begun to distinguish and experimentally explore the relationship between event construal (mechanisms of ‘attention direction’ that help (re)direct attention toward certain aspects of a situation reflecting the speakers’ ability to adjust) and event description (differential selection of linguistic resources for verbal encoding). The systematic investigation of verbal and non-verbal data now shows a surprisingly tight temporal coupling between these two types of behavior (Gleitman et al., Reference Gleitman, January, Nappa and Trueswell2007) with a large overlap between conceptualization and planning processes (but see Griffin & Bock, Reference Griffin and Bock2000, for a sequential account of processes at the conceptualization and formulation levels).
Studies examining various types of non-verbal behavior (e.g., memory, categorization, eye-movements) beyond verbal production present rather divergent results. Some report either no language effect on cognition or effects that are not clear and/or viewed as being superficial (Landau & Lakusta, Reference Landau, Lakusta, Hickmann and Roberts2006; Papafragou et al., Reference Papafragou, Massey and Gleitman2002, Reference Papafragou, Massey and Gleitman2006). Others find language-specific differences in non-linguistic measures captured immediately after verbalization (e.g., Gennari et al., Reference Gennari, Sloman, Malt and Fitch2002; Naigles & Terrazas, Reference Naigles and Terrazas1998; Slobin, Reference Slobin, Maeder, Fischer and Herlofsky2005) and/or when linguistic forms are recruited for explicit encoding (Papafragou et al., Reference Papafragou, Hulbert and Trueswell2008; Papafragou & Selimis, Reference Papafragou and Selimis2010), suggesting that the nature or the demands of the task may affect differently the language–thought interaction (see also Soroli et al., Reference Soroli, Hickmann, Hendriks, Aurnague and Stosic2019, for a recent discussion). For example, preparing to speak (in a verbal production task) constrains not only which components speakers choose to express but also how they allocate visual attention to these components very early during the visual processing of an event (e.g., Flecken et al., Reference Flecken, von Stutterheim and Carroll2014; Soroli et al., Reference Soroli, Hickmann, Hendriks, Aurnague and Stosic2019). Being instructed to provide a verbal output or process verbal material leads the viewer/speaker to focus on relevant aspects of the scene for sentence planning and sentence comprehension right from the start of stimulus onset and in order to optimize the uptake – the selection of the most adequate construal (for a review, see Divjak et al., Reference Divjak, Milin and Medimorec2020; Griffin, Reference Griffin, Henderson and Ferreira2004; Meyer & Lethaus, Reference Meyer, Lethaus, Henderson and Ferreira2004). The focus on relevant aspects of a scene is typically captured by gaze measures such as eye-fixations (e.g., numbers and duration of fixations), commonly used to study cognitive processing, attention allocation, intentions, and more generally the on-line strategies of the viewers (e.g., Park et al., Reference Park, Lee, Lee, Chang and Kwak2016).
Despite the fact that many studies that involve preparation for speaking or processing of verbal input tasks report robust effects on how people allocate their visual attention, little is still known about attention allocation when language is not explicitly involved during non-verbal tasks (non-verbal input and output) or the relative weight of language in relation to other factors that may create different pressures on on-line processing. For example, some studies have shown that the impact of language-specific features on event exploration depends on the nature of the scenes in which an event occurs. More specifically, in a preliminary study using two types of stimuli (animated cartoons and video clips) Soroli and Hickmann (Reference Soroli, Hickmann, Marotta, Lenci, Meini and Rovai2010) found differences in production as well as eye-tracking measures not only as a function of language but also as a function of scene types. Similar results are also reported by Hickmann et al. (Reference Hickmann, Engemann, Soroli, Hendriks, Vincent and Ibarretxe-Antuñano2017) as well as by Henderson and Ferreira (Reference Henderson, Ferreira, Henderson and Ferreira2004), suggesting that the placement and duration of gaze fixations may depend on the specific kinds of visual information to be processed during and even before verbalization.
Some studies focus on the relative impact of different types of motion components, raising more specific questions about the exact features that induce cross-linguistic variation in verbal and non-verbal processing, underlining the need for a fine-grained analysis of event types. For example, different types of Path (cf. Ibarretxe-Antuñano, Reference Ibarretxe-Antuñano, Guo, Lieven, Budwig, Ervin-Tripp, Nakamura and Özçalışkan2009; Talmy, Reference Talmy2000) and Manner (cf. Slobin et al., Reference Slobin, Ibarretxe-Antuñano, Kopecka and Majid2014) constrain to different degrees attention to specific dimensions of events even within a given language. According to Talmy (Reference Talmy2000) and Ibarretxe-Antuñano (Reference Ibarretxe-Antuñano, Guo, Lieven, Budwig, Ervin-Tripp, Nakamura and Özçalışkan2009), Path is the most basic component defining motion, and its relative salience in a given language affects speakers’ verbalizations to different degrees. Slobin et al. (Reference Slobin, Ibarretxe-Antuñano, Kopecka and Majid2014) consider that the major distinctive feature that determines the likelihood and lexical richness of spatial expressions in a system is the salience of Manner instead. Soroli (Reference Soroli2011) also shows that particular features of Manner, including Manner of motion with an instrument (e.g., cycling) or without (running), constrain differently behavior across language groups, for example, inducing richer Manner expression in English than in French, even in unmarked co-events, such as walking (prototypical Manner of movement for humans) (but see also Hickmann et al., Reference Hickmann, Engemann, Soroli, Hendriks, Vincent and Ibarretxe-Antuñano2017).
The assumption that different languages and spatial event properties or types of scenes contribute to different ways of conceptualization options needs, however, further specification and careful operationalization. For example, in the domain of spatial language and cognition some studies report great variability with respect to the type of stimuli used. For example, Hickmann et al. (Reference Hickmann, Engemann, Soroli, Hendriks, Vincent and Ibarretxe-Antuñano2017), who used animated cartoons in their design, surprisingly report strong Manner saliency with walking events and fail to replicate findings from other similar studies that use real-motion video events and suggest low saliency for this kind of motion (cf. Flecken et al., Reference Flecken, von Stutterheim and Carroll2014; Soroli, Reference Soroli2012). Hickmann and colleagues further discuss the possibility that different types of stimuli (video/cartoons) may induce differences in the sensitivity to specific event properties and lead to misleading results. They admit that although cartoon-like stimuli allow to control for many variables (neutralization of moving backgrounds, control of contrast and speed for better identification of target figures and motion properties, etc.), cartoons are not as ‘ecological’ as other types of stimuli such as recorded films of natural motion in real settings and over-attract the viewer during processing. Similar inconsistencies are reported with material that uses human versus animal motion. With respect to this point, what can be prototypical and unmarked for human motion in terms of affordances (e.g., walking) may be highly salient and artificial for an animal motion event, as nonhuman animals do not walk, at least not as humans do (cf. Gibson, Reference Gibson1979).
To conclude, more fine-grained research is necessary to avoid the tendency of some studies to overgeneralize motion material processing (with cartoon-like/video motion, human/nonhuman) to any kind of motion processing and to constrain analysis in one of two ways: (1) by exclusively focusing on Manner or Path salience and (2) by simplifying event properties at the risk of proposing partially misleading conclusions, for example, by reducing Manner of motion to easy distinguishable but rather artificial body movements (e.g., use of figures without limbs; see Bohnemeyer et al., Reference Bohnemeyer, Bowerman, Brown, Levinson and Enfield2001; Montero-Melis et al., Reference Montero-Melis, Eisenbeiss, Narasimhan, Ibarretxe-Antuñano, Kita, Kopecka, Lüpke, Nikitina, Tragel, Florian Jaeger and Bohnemeyer2017) or by reducing Path to only one of its components (e.g., use of Endpoints; see Carroll & von Stutterheim, Reference Carroll, von Stutterheim, Bohnemeyer and Pederson2011; Papafragou et al., Reference Papafragou, Hulbert and Trueswell2008).
1.3. Aims, research questions, and predictions
Although most approaches agree that typological differences affect speakers’ verbal behavior, there is no consensus about the contexts in which such differences arise, which specific levels of verbal encoding are most influenced by such differences, and whether they also affect non-verbal behavior. More specifically, the aim of this paper is to examine the language–cognition relationship by investigating (i) whether the differences in two typologically contrasted languages (English and French) constrain participants’ verbal and non-verbal performance; (ii) whether any variation in performance depends on differences in event types (with varied degrees of saliency of Path/Manner) and/or scene types (natural vs. artificial/cartoon-like voluntary motion sets); (iii) whether typological differences are reflected across encoding dimensions (semantic, lexical/morphosyntactic, utterance levels); and (iv) more importantly, whether any cognitive influences (during attention allocation and decision-making) arise both when language is and is not explicitly involved.
According to a first strong universalist hypothesis, language and cognition are two autonomous systems; thus, participants’ native language should not have an influence on the on-line processing of spatial scenes (neither on attention allocation patterns nor on decision-making). According to a strong relativistic hypothesis, language and cognition constantly interact; thus, the specific properties of individual languages, together with other external perceptual features, should leave their traces in all tasks and measures (verbal and non-verbal). According to a more moderate relativistic hypothesis, any potential language effects should only occur in tasks involving (or requiring the processing of) explicit linguistic information or in perceptually salient contexts (e.g., scenes that involve non-prototypical or artificial events such as jumping or crawling humans, cartoon-like motion, etc.).
2. Method
2.1. Participants
A total of 49 native speakers were tested, and 40 participants were included in the analysisFootnote 5 (20 participants per language and per experiment), half males and half females with comparable socioeconomic status. Participants were all university students, native, monolingual speakers of English or French, right-handed, above 18 years of age, and without any known acquired or developmental disorder. They all had early exposure to only one language, had not spent more than six months in a foreign country, and eventually learned (if any) a second language after the age of 10 (compulsory teaching at school). The recruitment and testing of the participants took place in two universities: English speakers were tested at Cambridge University (United Kingdom) and French speakers at the University of Paris (France). The participants received course credit compensation for their participation.
2.2. Materials and procedure
The participants were tested in three experiments involving different types of voluntary motion events executed in different Manners (with and without instruments) and along different Paths (with and without boundary crossings) and in tasks involving language to different degrees, all coupled with an eye-tracking paradigm. Participants’ eye-movements during stimuli exploration were recorded with a Tobii X120 system that was placed in front of an 18,4″ laptop monitor at a distance of about 70 cm from the participants.
Experiment 1 was a non-verbal categorization task in which participants had to perform non-verbal similarity judgments. They first watched a fixation cross (+) on the screen and then had to watch a 4-second target video film depicting a natural human voluntary motion event followed by a beep and two video variants: a variant depicting a similar Manner-congruent event and a variant depicting a similar Path-congruent event. They had to choose among the two variants the video clip that looked most like the target, as fast as possible (Figure 2). In total, 54 triads of this type were presented: 3 training items; 7 distractors involving motion of inanimate objects; 14 control items in which one of the variants was Manner- or Path-congruent to the target but performed by another figure; and 30 experimental items involving voluntary motion events in 5 types of Path (involving or not the presence and crossing of a boundary with and without a change of state) × 3 types of Manner (with instruments, without instruments, and a default-Manner of motion) × 2 versions/exemplars (each Manner–Path combination was presented in two versions: one performed by a man and one performed by a woman).Footnote 6
Figure 2. Non-verbal categorization task: example of an experimental item involving a target (jump-out-of) and two variants: jump-into (Manner congruent) versus walk-out of (Path congruent).
More specifically, the different Manners and Paths were selected with the following rationale. Manners varied along a continuum from the most to the least salient Manner of moving for humans – riding a bicycle, riding a scooter, roller skating > crawling, jumping, running > walking – and were expected to have different effects on attention allocation and non-verbal behavior in general. For example, Manners involving instruments were expected to be the most attractive ones for the viewers (following Hickmann et al., Reference Hickmann, Engemann, Soroli, Hendriks, Vincent and Ibarretxe-Antuñano2017; Slobin et al., Reference Slobin, Ibarretxe-Antuñano, Kopecka and Majid2014), while the least attractive and, consequently, the least salient were expected to be the most prototypical ones in terms of natural human affordance (walk) – a way of moving that we do not necessarily attend to as it is typically inferred/presupposed to be present by default. Paths included some displacements that involved the crossing of intrinsic boundaries and some that did not. They were selected also with respect to their relative salience (change of location with the presence/absence of a boundary, crossing/or not of the boundary, and involvement/or not of a change of state): single-boundary-P into/out-of (change of location + presence of a boundary + crossing of the boundary + change of state) > double-boundary-P across (change of location + presence of a boundary + crossing of a boundary − no change of state) > double-boundary-Default-P along (change of location + presence of a boundary − no boundary crossing − no change of state) > no boundary at all-vertical motion up/down (change of location − absence of a boundary − no boundary crossing − no change of state). The presence of intrinsic boundaries, their crossing, and their eventual combination with a change of state (e.g., into/out-of items) were expected to maximally attract speakers’ attention to Path in both groups, but to a greater extent in French given its Path-based (verb-framed) lexicalization pattern.
Experiment 2 (verbal version of experiment 1) was a verbal categorization task, during which participants had to perform similarity judgments. They were presented with the same video set but first heard a target sentence instead of watching a target video – a construal encoding both Manner and Path (e.g., There is someone walking in/On voit quelqu’un qui entre en marchant) – and then had to choose among two video clips the variant best described by the sentence.
In experiment 3, participants had to describe voluntary motion scenes in a production task. The first set consisted of the same short video clips in which a human agent (man or woman) performed displacements indoors or outdoors, in varied Paths and Manners. The second set of stimuli (hereafter cartoons) consisted of short animated drawings showing different figures (animals and humans) moving along three types of Paths (up, down, and across), in different Manners (e.g., climbing, swimming, walking), and within varied background settings (e.g., a mouse climbing up a table – Figure 3). A total of 35 items were presented: 2 training items, 28 experimental items (10 video clips and 18 cartoons), and 5 distractors.Footnote 7 Stimuli from both sets were scattered in a randomized list that equally distributed the distractors every five items in a mixed set that differed from one participant to the other. Participants first watched a fixation cross in the middle of the screen, then watched a clip followed by a beep and a blank/white screen, and finally had to describe what happened in the clip.Footnote 8
Figure 3. Areas of interest for events without boundary crossing (up/down) – cartoon scenes.
2.3. Coding
2.3.1. Linguistic data
The verbal responses collected during experiment 3 (production task) were coded for the main motion components expressed (focus), for the linguistic means used to encode them (locus), and for the ways these components were organized in utterances (architecture). As illustrated in (3)–(7), responses fell into five groups, depending on their focus: only Manner (M), only Path (P), both components (PM), or neither (Z for simple motion verbs like go/get, as in (7)), as well as some rare cases where speakers did not provide any response or expressed some other spatial information considered as irrelevant, such as simple locative expressions or Cause (coded: NR).
The locus analysis distinguished between verb versus other peripheral devices and the spatial components expressed in them (e.g., Manner verb in (3); Path verb in (4), Manner verb + Path peripheral device in (5) versus fused Path + Manner verb in (6)). The architecture analysis focused on how spatial components were packaged or distributed in the utterances: Tight simple (TS) constructions consisted of one simple, independent clause that encoded both the framing and the co-event in a compact structure (8); tight complex (TC) constructions contained at least one dependent clause or gerund (9); loose simple (LS) constructions were constructions in which information was spread over at least two juxtaposed or coordinated clauses (10); and loose complex (LC) constructions were constructions in which information was expressed in two or more clauses with at least one dependent element (11).
The prediction was that speakers’ descriptions would reflect the typological features of their language: They were expected to (a) express Manner (in the verb) and combine it with Path (in other devices) more frequently in English than in French and (b) use syntactically simpler and semantically more compact (TS) constructions in English than in French.
2.3.2. Categorization data
In the experimental items of the two categorization tasks (experiments 1 and 2), there was no correct answer. In order to check for unmotivated, biased, or random responses, control items were inserted in the tasks, in addition to the distractor items. The data collected within these experiments were analyzed with particular attention to (a) the number of correct responses (accuracy rates) in the control items; (b) variation in Manner-congruent choices across and within groups and item types in the experimental items; (c) reaction times (RTs) (in milliseconds) from stimuli onset until participants’ response; (d) the fixation counts to specific areas of interest (AoI) (Path vs. Manner areas); and the fixation lengths to those areas (in milliseconds).
2.3.3. Eye-tracking data
Participants’ eye-movements were recorded while participants were exploring the scenes – the video variants in experiments 1 and 2 and the main video and cartoon clips in experiment 3 – in such a way as to measure their attention allocation to various aspects of motion events during decision-making and before verbalization, respectively. In order to better capture the dynamic nature of eye-movements, the coding of these data was not limited to static dimensions, such as the posture of the figure (for Manner) or the Endpoints of motion (for Path) as was done in most previous studies. Rather, spatially distinct components were defined in such a way as to represent dynamic areas during the actual displacement. As illustrated in Figures 3 and 4, the stimuli were divided into AoI, the coding of which corresponded to specific features of the event:
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(a) Path areas (S, P, G): Following Talmy’s definition, Path was divided into three parts – an initial, an intermediate (median), and a final region, each one corresponding to an AoI: Source (S), (P), and Goal (G), respectively. Fixations were coded as Pbroad fixations (dashed area in Figures 3 and 4) when they fell into the three S-, P-, and G-AoI, excluding the moving limbs of the figure (the other half of the target scene covering the legs, see Manner area in (b)).
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(b) Manner area (P ± M): Eye-movements to areas corresponding to the legs of the moving figures and to instruments were considered as (mainly) Manner fixations even if these areas also involved some aspects of the traced trajectory.
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(c) Additional M-congruent versus P-congruent areas were distinguished for the video variants involved in experiments 1 and 2 that corresponded to the Manner-congruent and Path-congruent choices the viewers were presented with, respectively.
Figure 4. Areas of interest for single-boundary-crossing events (into/out-of) – video clips.
The analysis of fixations involved measures of counts (numbers of fixations) and lengths (durations) but also more qualitative evaluations of the gaze scanpaths (gazeplots). Typically, fixation counts are indicators of the efficiency of information search and uptake during visual scanning; fixation lengths are measures that indicate attention maintenance; and gazeplots provide information about attention distribution and decoding complexity (more steps in the scanning process relate to more cognitive load) (Holmqvist et al., Reference Holmqvist, Nyström, Andersson, Dewhurst, Jarodzka and Van de Weijer2011).
According to the typological hypothesis, English viewers were expected to be more sensitive to Manner distinctions and thus focus more and longer on areas involving Manner (P ± M) than French viewers. In addition, although all viewers were expected to focus on Path (Pbroad areas), French viewers were expected to fixate these areas more often and for a longer duration. A main distinction was made between AoI that involved mostly Manner and those that did not. The analysis of Path fixations was twofold: First, Path fixations were considered separately (e.g., fixations falling into S-, G-, and P-AoI) in order to obtain their relative distribution across Path areas defined in the scenes; then, a distinction was made between P and Pbroad fixations: the first corresponding to an analysis that considered only fixations that fell to the intermediate P area and the latter to an analysis that merged fixations falling to intermediate P together with fixations to S and G parts (marked in dashed lines in the Figures above). The anonymized quantitative summaries of the data used for the analyses can be found at https://osf.io/2hdxg/?view_only=9408ab7e47844ed2b302ef5eedc621b3.
3. Results
3.1. Verbal measures
The productions collected during experiment 3 were analyzed in several ways in order to determine which motion components were expressed (focus), with which linguistic means (locus, particularly main verbs vs. other devices), in which structures (architecture), and with which types of scenes. Separate analyses of variance (ANOVA) for videos and cartoons examined the effects of language (as between-subject factor) and of core-event-type (as within-subject factor) on several dependent variables.
3.1.1. Focus of information
For cartoons, as expected, PM responses were more frequent in English (83%) than in French (42%) where speakers expressed more often Path alone (55%). Mixed ANOVA examined the effects and interactions of the language factor (English, French) and of the core-event-type factor (up, down, across, along events) on PM responses.Footnote 9 The results show significant main effects of language (F(1,36) = 75.50, p < 0.0001) and of core-event-type (F(3,108) = 37.62, p < 0.0001), as well as a significant interaction between these two factors (F(3,108) = 8.27, p < 0.0001). Additional specific contrasts between boundary-crossing events (across) and displacements without boundary crossing (up and down) show that P-only responses were mostly given by French participants, as opposed to the systematic PM responses of English participants (Figure 5). When French participants provided either fused or distributed PM responses, it was mostly with double-boundary crossings (across) and vertical (upward) events: PM responses with across events were more frequent than with up (F(1,18) = 5.67, p = 0.02) or down events (F(1,18) = 153.72, p < 0.01) and PM responses with up events were significantly more frequent than with down events (F(1,18) = 49.78, p < 0.001). In English, similar differences occurred in speakers’ PM responses, except that PM responses with up and down events did not differ significantly (up < across: F(1,18) = 9.26, p < 0.01, down < across: F(1,18) = 11.08, p < 0.01, but up vs. down: p = 0.13 ns). French speakers’ PM responses in across events were mostly due to distributed P and M encodings and in up events to uses of some verbs such as grimper (‘to climb up’), which lexicalize both upward motion and Manner in a monomorphemic way (12).
Figure 5. Focus of verbal responses across languages and core-event-types – cartoons.
With respect to the focus of speakers in the video set, the analysis showed again significant main effects of language (F(1,36) = 24.04, p < 0.0001) and core-event-type (F(5,180) = 5.84, p < 0.0001), as well as an interaction between these two factors (F(5,180) = 5.02, p < 0.001). While overall PM responses were still significantly more frequent in English (92%) than in French (76%), speakers showed a general preference for PM responses in both languages, even in French where P-only responses with these items were quite rare (22%). As illustrated in Figure 6, further analyses showed that PM conflation in the video scenes was mostly due to single-boundary-crossing events (out-of items: 26% and into items: 21%) in both language groups and that the language effect stemmed mainly from the strong preference of English speakers to encode both Path and Manner, especially with into (F(1,36) = 14.59, p < 0.001) and across (F(1, 36) = 6.08, p = 0.01) events, as opposed to French speakers who did so but to a lesser extent.
Figure 6. Focus of verbal responses across languages and core-event-types – videos.
3.1.2. Locus of information
In order to examine the effects and interactions of the three main factors (language, core-event type, and locus) on the expression of P, M, and PM components with cartoon items, three mixed ANOVA were performed. The analysis showed significant main effects of language (except for PM, see below), core-event-type, and locus(verb vs. other devices). More specifically, the expressed components varied significantly as a function of locus (PM: F(1,36) = 63.63, p < 0.0001; P: F(1,36) = 90.11, p < 0.0001; M: F(1,36) = 337.39, p < 0.0001) and core-event-type (PM: F(3, 108) = 15.30, p < 0.0001; P: F(3,108) = 122.68, p < 0.0001; M: F(3, 108) = 106.55, p < 0.0001). Collapsing languages, verbs encoded either Manner (45%) or Path (38%) and only rarely both (10%), while other devices encoded mostly Path (68%). However, the locus for P and M components (but not for their combination) also varied significantly as a function of language (M: F(1,36) = 75.06, p < 0.0001; P: F(1,36) = 26.91, p < 0.0001; PM: ns). Figure 7 illustrates the distribution of the spatial components in verb and other devices as expressed by the two language groups: French speakers mainly encoded Path information in the verb (74%), sometimes double-marking it in peripheral devices as well (43%) or without any other information in the periphery (37%), and only rarely expressed Manner in the verb (6%) or in the periphery (18%). In contrast, Manner information was expressed massively in the main verb by the English speakers (84%), systematically combined with other linguistic devices that encoded Path (92%), as expected. Further analyses showed a significant interaction between locus and core-event-types (PM: F(3,108) = 16.24, p < 0.0001; P: F(3,108) = 7.27, p < 0.001; M: F(3,108) = 32.99, p < 0.0001). Speakers only rarely conflated both Path and Manner components in verbal devices (less than 20%), and when they did so, it was mostly the French speakers who opted for such conflations, especially with upward motion events (16%). Manner was encoded more often by the English speakers and lexicalized with across > up > down events (32%, 29%, and 23%, respectively), while Path lexicalization was more frequent in the French encodings, especially with down > across > up events (32%, 26%, and 16%, respectively).
Figure 7. Locus of spatial information as expressed in verbs (V) and other devices (OTH) across languages – cartoons.
Figure 8 illustrates how the target spatial components were distributed across different loci with videos. The analyses with this type of scenes showed again a significant main effect of core-event-type but only a partial language and locus effect. More specifically, although the expression of all three components varied as a function of core-event-type (PM: F(5,180) = 9.37, p < 0.0001; P: F(5,180) = 37.80; p < 0.0001; M: F(5,180) = 2.69, p = 0.02), only P and M encodings varied significantly as a function of locus (P: F(1,36) = 93.19, p < 0.0001; M: F(1,36) = 31.23, p < 0.0001; PM: ns) and as a function of language (P: F(1,36) = 16.36, p < 0.001; M: F(1,36) = 4.85, p < 0.05; PM: ns). In French, as predicted, speakers mainly expressed Path in the verb (78%) and some Manner outside of the verb (29%). In contrast, English speakers systematically encoded Manner in the main verb (87%) and Path in the periphery (86%). Finally, the locus of information interacted with the core-event factor in the videos (PM: F(5,180) = 5.06, p < 0.01; P: F(5,180) = 8.15, p < 0.0001; M: F(5,180) = 17.80, p < 0.0001). Conflation of both Path and Manner components was relatively infrequent and mainly occurred in peripheral devices (36% in French and 14% in English).
Figure 8. Locus of spatial information as expressed in verbs (V) and other devices (OTH) across languages – videos.
3.1.3. Architecture
Figures 9 and 10 show how speakers decided to package spatial information in different types of constructions (TS, TC, LS, and LC) with cartoon and video scenes, respectively. A mixed ANOVA examined the effects of language and core-event-type on TS scores. The results show significant main effects of language (in both cartoons and videos: F(1,36) = 37.33, p < 0.0001, and F(1,36) = 146.96, p < 0.0001, respectively) and of scene types (cartoons: F(3,108) = 38.64, p < 0.0001; videos: F(5,180) = 20.43, p < 0.0001). As expected, TS responses were overall significantly more frequent in English (91% and 94%, respectively) than in French (75% and 39%), while TC responses were more frequent in French than in English, but only with the videos (49% vs. 2%). Further analysis revealed language effects with some core-event-types: (a) TS constructions were used in the cartoon set significantly more frequently in English than in French with double-boundary-crossing/across items (89% vs. 46%, F(1,36) = 101.03, p < 0.0001), but not with up/down events; (b) in the video set, significant language effects occurred with all boundary-crossing events: single-boundary crossing such as into (F(1,36) = 73.48, p < 0.0001) and out-of items (F(1,36) = 103.10, p < 0.0001) and double-boundary crossings with across items (F(1,36) = 72.00, p < 0.0001) as well as with down events (F(1,36) = 104.04, p < 0.0001).
Figure 9. Response architecture with cartoons.
Figure 10. Response architecture with videos.
To summarize, although overall compact constructions (TS) were the most frequent across languages and stimuli sets, some variation is noted in motion expression with some scenes (e.g., videos) and core-event-types (e.g., single-boundary-crossing items). More specifically, although English speakers systematically expressed Manner in verbs together with Path in other devices within the same compact structures and across stimuli sets, as in (13a,b), French speakers’ motion descriptions followed the prototypical (one lexicalized core component) pattern, focusing on Path, lexicalized in verbs within TS constructions, and omitting Manner information, but only with the cartoon set, as in the example (13c). With the video set, Path primacy was not that evident for French speakers. With these items that involved exclusively natural human voluntary motion events, French speakers tended to add quite frequently Manner information in their utterances by means of other devices and thus organize them within TC constructions and some LS constructions, as in (13d) and (13e), respectively. This phenomenon occurred especially with non-default-Manners (such as run, jump, ride a scooter, ride a bike, roller skate) and especially with one-boundary-crossing events (into/out-of), which involved a change of state (invisible/visible figure/agent – cf. Slobin, Reference Slobin, Hickmann and Robert2006): an agent enters (appears) and exits (disappears), respectively, in these items, inviting the speaker to specify the particular way (the Manner) this change of state occurs, if necessary/salient, with the addition of some peripheral devices (e.g., en courant/à toute vitesse ‘running/in all speed’, en sautant/pieds joints ‘by jumping/with joint feet’, à vélo ‘on a bike’, en rollers ‘on roller skates’, avec une trottinette ‘with a scooter’) or with the distribution of components across clauses (e.g., coordination). Partly, this tendency to add Manner within the video set can also be explained by the fact that two of the above-mentioned salient Manners (riding a scooter and jumping events) were present in this set but not in the cartoon set.
To conclude, although these results are in line with the general prediction that language-specific properties affect different aspects of speakers’ verbal behavior (focus, locus, architecture) supporting the typological asymmetry documented in prior experimental and theoretical studies, the findings further suggest within-language variation in the verb-framed language (French). More specifically, with some scenes that involve human natural motion (videos) and in which the Manner of motion is not the prototypical one for humans (walking) and/or the core event involves a change of state (e.g., single-boundary-crossing events), French invites speakers to add Manner specifications and organize relevant information in more distributed ways, with TC and LS, as in (13d) and (13e) respectively.
3.2. Non-verbal measures
Experiments 1 and 2 involved 14 control items each, in which one of the variants corresponded to a correct answer (either Manner or Path congruent to the target but performed by another figure). The analysis of the control items showed ceiling performance in the responses of the participants allowing to move on to the analysis of the non-verbal measures in the experimental items of these tasks: similarity judgments and RTs.Footnote 10
3.2.1. Similarity judgments
The framing event involving Path (considered as the core spatial component, according to Talmy) was expected to be the main similarity judgment criterion in the responses of all participants. Any language difference was expected to emerge with respect to the non-core component of events (Manner). Thus, the similarity judgment data were analyzed using mixed ANOVA on Manner responses, including gender (male, female)Footnote 11 and language (French, English) as across-subject factors and Path-item-type and Manner-item-type as within-subject factors. An additional ANOVA was conducted to evaluate the global sources of variation across tasks with a categorization-type variable (non-verbal/CatNV, verbal/CatV) as an additional within-subject factor. The analysis showed first a significant categorization-type effect, in that Manner choices were significantly more frequent in the verbal task than in the non-verbal one (F(1,36) = 57.42, p < 0.0001). With respect to the main language factor, all ANOVA revealed a significant language effect across tasks (F(1,36) = 16.71, p < 0.001) as well as within each task (non-verbal: F(1,36) = 7.03, p = 0.01; verbal task: F(1,36) = 17.42, p < 0.001). As expected, Manner-congruent variants were chosen almost twice more frequently by the English participants. More specifically, the mean was calculated by recording the number of Manner matches out of 20 individuals in each group. Figure 11 illustrates the mean number of Manner-congruent choices as performed by French and English participants in the non-verbal and verbal tasks. In the non-verbal categorization task (CatNV/experiment1), although French participants were clearly guided by the Path-congruency in the variants (P congruent: 78%; M congruent: 22% of their choices), the English participants were guided much less by this criterion (P-congruent: 59%; M-congruent responses: 41%), and analogously, Manner choices were significantly more frequent in the English dataset than in the French one. With respect to the similarity judgments in the verbal categorization task (CatV/experiment2), the results show that Manner-congruent choices were selected more frequently in the verbal task than in the non-verbal one by both French (F(1,18) = 26.14, p < 0.001) and English (F(1,18) = 31.30, p < 0.001) participants; however, French participants continued to show stronger Path-congruent preferences and significantly less Manner-guided choices (P: 59% vs. M: 41%) as compared to the English participants (M: 67% vs. P: 33%, (F(1,36) = 16.71, p < 0.001).
Figure 11. Mean number of Manner choices by French and English participants across categorization tasks.
Note: Error bars indicate mean ± SE.
Further comparisons showed two significant item type effects within and across tasks: an effect of Path-item-type (non-verbal task: F(3,108) = 7.43, p < 0.001; verbal: F(3,108) = 47.82, p < 0.001; across tasks: F(3,108) = 27.16, p < 0.001) and an effect of Manner-item-type (non-verbal task: F(2,72) = 6.39, p < 0.01; verbal: F(2,72) = 18.481, p < 0.001; across tasks: F(2,72) = 4.38, p = 0.01), as well as a significant interaction of these two factors (Path X Manner) in the non-verbal task (CatNV), in the verbal (CatV), and across tasks (CatNV: F(6,216) = 5.82, p < 0,001 CatV: F(6, 216) = 5.79, p < 0.001; across tasks: F(6,216) = 9.60, p < 0.001). More specifically, with respect to the Manner-item-type effect, in CatNV, Manner-congruent variants were chosen more often when targets involved either Manner-without-instrument (jump, run, etc.) or default-Manner (walk) as compared to Manner-with-instrument (cycle, roller skate, etc.): default-M versus M-with-instr.: F(1,36) = 5.03, p = 0.02; M-without- versus M-with-instrument: F(1,36) = 15.55, p < 0.001. In the CatV, however, the Manner-congruency criterion was chosen more often when targets involved Manner-with-instrument as compared to the other two item types (M-with- vs. M-without-instrument: F(1,36) = 14.58, p < 0.001; M-with- vs. default-M: F(1,36) = 31.22, p < 0.001). Further tests carried out within each language showed additional variation stemming from the Manner type of the items. More specifically, although in French a Manner-item-type effect was found both in the non-verbal task (F(2,38) = 6.36, p < 0.01) and in the verbal task (F(2,36) = 7.12, p < 0.01), in the English responses the Manner-item-type effect appeared only in the verbal one (F(2,36) = 11.93, p < 0.001). More specifically, partial comparisons within French responses in the non-verbal task revealed that items that involved either default-Manner or Manner-without-instrument events elicited more Manner choices than motion events that depicted Manner-with-instrument (default-M vs. M-with-instr.: F(1,18) = 8.56, p < 0,01; M-without-instr. vs. M-with-instr.: F(1,18) = 11.37, p < 0,01). In contrast, in English, only the comparison between Manner-without- and Manner-with-instrument was significant (F(1,18 = 4.99, p = 0,03), with Manner-congruent choices being more frequent with the first type (items without instruments) than with the latter (items with instruments), as illustrated in Figure 12. Further tests across languages revealed significant language differences with Manner-with-instrument (F(1,36) = 10.36, p < 0,01) and Manner-without-instrument event types (F(1,36) = 6.58, p = 0.01) in the non-verbal task and with all Manner types in the verbal task (default-M: F(1,36) = 9.36, p < 0,01; M-without-instr.: F(1,36) = 15.38, p < 0,001; M-with-instr.: F(1,36) = 13.15, p < 0.001).
Figure 12. Proportion of Manner choices across different Manner-item-types in French (A) and English (B).
Further item type comparisons revealed significant differences in the Manner choices of the participants as a function of different Path types. Overall, Manner choices were more frequent with one-boundary-crossing events (into/out-of) and two-boundary-crossing (across) Paths than with default (along) and vertical (up/down) ones. More specifically, and as illustrated in Figure 13, Manner-congruent choices in the non-verbal task were more frequent in French with one- and two-boundary-crossing events as compared to default and vertical Paths (e.g., one-boundary-P vs. vertical-P: F(1,18) = 6.08, p = 0.02; two-boundary-P vs. vertical-P: F(1,18) = 5.23, p = 0.03) with an additional significant increase in Manner choices with default-P (along) items (e.g., default-P vs. one-boundary-P: F(1,18) = 41.41, p < 0.0001). Partial comparisons in the English responses showed that Manner choices were more frequent when one- or two-boundary-crossing events were involved in the targets, in both tasks, as compared to vertical- and default-Path (along) items (e.g., one-boundary-P vs. vertical-P: F(1,18) = 8.40, p < 0.01; two-boundary vs. default-Path: F(1,18) = 4.66, p = 0.04). Additional tests across languages within specific Path types in the targets showed significant language differences, as well: The Manner-congruency criterion was preferred again significantly more often by the English participants than by the French, especially with vertical (F(1,36) = 8.02, p < 0,01) and one-boundary-crossing events (F(1,36) = 6.69, p = 0.01) in the non-verbal task, and more broadly with vertical (F(1,36) = 30.47, p < 0.001), one-boundary-crossing (F(1,36) = 15.32, p < 0.001), and two-boundary-crossing (F(1,36) = 16.96, p < 0.001) events in the verbal task.
Figure 13. Proportion of Manner choices across different Path-item-types in French (A) and English (B).
3.2.2. Reaction times
In experiments 1 and 2, the overall RTs to target video clips were analyzed with a mixed ANOVA with gender (male, female)Footnote 12 and language (French, English) as across-subject factors and Path-item-type and Manner-item-type as within-subject factors. An additional ANOVA was conducted to evaluate the global sources of variation across tasks with a categorization-type variable (non-verbal/CatNV, verbal/CatV) as an additional within-subject factor. The analysis showed first a significant categorization-type effect (F(1,36) = 40.74, p < 0,001), in that RTs for the selection of Manner-congruent variants were overall significantly longer in the verbal than in the non-verbal task. Figure 14 presents the mean RTs for Manner-congruent choices of participants across tasks (Figure 14). A mixed ANOVA with language as between-subject factor and Manner- and Path-item-types as within-subject factors revealed a statistically significant main effect of both Path- and Manner-item-types (F(2,72) = 19.23, p < 0.0001; and F(3,108) = 9.05, p < 0.0001, respectively), as well as a statistically significant interaction between these two factors (F(6,216) = 6.28, p < 0.0001) but no language effect.
Figure 14. Mean reaction times on M choices of French and English participants across categorization tasks (error bars indicate mean ± SE).
With respect to item types, in the non-verbal task, participants took significantly more time to select a variant when exposed to a target item that did not involve any instrument (default-M and M-without-instrument motion) and spent more time with items that involved instruments during the verbal task (task-type effect with default-M targets: F(1,36) = 30.41, p < 0,001; M-without-instr.: F(1,36) = 31.17, p = 0.001; and M-with-instr.: F(1,36) = 49.46, p < 0,001 but no language effect across groups). With respect to the Path-item-type factor, partial comparisons reveal a main Path-item-type effect in the non-verbal task, for both English and French Manner responses (F(3,54) = 13.16, p < 0.0001; F(3,54) = 4.44, p < 0.001, respectively), but not in the verbal task. Specific comparisons between different item types showed that in the non-verbal task, the items that required more processing time were those involving one-boundary crossing, then those involving vertical motion, and finally those involving either default- or double-boundary crossing, while in the verbal categorization there was no significant variation across Path types. Overall, the analysis shows that differences in the mean RTs of French and English-speaking participants were statistically different across groups only in the verbal task (experiment 2) in that Path-congruent choices took longer time to be selected by English participants as opposed to French (mean difference: 540, p < 0.0001), but this difference was only marginal with Manner-congruent variants (mean difference: 110, p = 0.05). Figure 15 summarizes the mean RTs of Path- and Manner-congruent choices in the two categorization tasks as performed by French and English participants.
Figure 15. Manner- and Path-congruent choices: reaction times (in msec) of French and English participants across categorization tasks.
3.3. Eye-movements
3.3.1. Production task
The analyses of eye-movements during verbalization (experiment 3) aimed to identify how speakers of typologically different languages not only encode but also allocate their attention to different visual components of motion events (gazes to Manner- and/or Path-related areas, treated as a within-subject factor) during construal selection.Footnote 13
Fixation counts. A mixed ANOVA examined first the effects and interactions of language, core-event-type (up, down, across), and AoI type (P ± M, P, S, G) on the number of fixations with cartoons. The analysis showed significant effects of language (F(1,36) = 9.04, p < 0.01) and AoI (F(4,144) = 203.25, p < 0.0001), as well as an interaction between these two factors (F(4,144) = 12.45, p < 0.0001). Further analysis showed that French participants fixated Pbroad areas (gazes on P + S + G) significantly more often than the English group (F(1,36) = 16.43, p < 0.0001). In contrast, Manner (P ± M) fixations showed no significant language difference (Figure 16).
Figure 16. Number of fixations to P ± M and Pbroad AoI with different item types in cartoon scenes.
Although no general effect of core-event-type was found in the cartoon set, this factor had a significant impact in relation to specific Manner and Path components involved in the stimuli. In particular, core-event-type had an impact on both Pbroad and P ± M fixations (F(2,72) = 52.38, p < 0.0001, and F(2,72) = 23.17, p < 0.0001, respectively), in that Manner fixations were more frequent with double-boundary-crossing (across) events, while Path fixations were more frequent with vertical ones (up and down). Nevertheless, fixations to different core-event-types did not differ significantly across the two language groups. With respect to the AoI effect, separate contrasts show that fixations were significantly more frequent on P-AoI as compared to the other AoI, as summarized below for cartoons:
$$ \mathrm{Fixation}\ \mathrm{counts}\ \mathrm{in}\ \mathrm{cartoons}:\mathrm{P}>\mathrm{P}\pm \mathrm{M}>\mathrm{G}=\mathrm{S} $$
A similar mixed ANOVA was carried out for video scenes. The analysis revealed again a main significant effect of language (F(1,36) = 8.51, p < 0.01) and of AoI (F(4,144) = 63,189053, p < 0.0001), as well as an interaction between these two factors (F(4,144) = 5.69, p < 0.0001). Fixations were more frequent on both P-, P ± M-, and G-AoI as compared to the S-AoI. Fixation counts can be summarized as follows for videos:
$$ \mathrm{Fixation}\ \mathrm{count}\ \mathrm{in}\ \mathrm{videos}:\mathrm{P}=\mathrm{P}\pm \mathrm{M}=\mathrm{G}>\mathrm{S} $$
Although with video scenes both language groups fixated Pbroad areas significantly more than P ± M areas (French: F(1,18) = 8.78, p < 0.01; English: F(1,18) = 15.32, p < 0.01), French participants fixated Pbroad areas significantly more than the English group (F(1,36) = 4.76, p = 0.03). P ± M fixations showed again no significant language difference. Although further analyses on fixation counts to Path and Manner areas revealed no global effect of core-event-type, this factor had a significant impact on specific AoI. As illustrated in Figure 17, this factor had an effect on both P ± M and Pbroad fixations (F(4,144) = 15.59, p < 0.0001; and F(4,144) = 5.48, p < 0.001, respectively) for both language groups: P ± M fixations were more frequent with vertical (no boundary) events (up and down); Pbroad fixations were more frequent with boundary-crossing events (into/out-of and across).
Figure 17. Number of fixations to P ± M and Pbroad AoI with different item types in video scenes.
To summarize, fixation counts varied as a function of AoI and of Path types in the videos and, in some cases, as a function of language group. Overall, fixations occurred more frequently on Path areas, particularly with vertical motion (both up and down) events, than on Manner areas, which were mostly associated with across in the cartoon set, as well as with across and down events in the video set. Surprisingly, the language effect initially predicted in relation to the salience of Manner (following the Manner cline proposed by Slobin) did not occur. P ± M fixations did not differ between English and French viewers. The only language effect observed concerned Path areas, in that French viewers fixated more frequently Path areas, as opposed to the English group, who did so to a lesser extent.
Duration of fixations. The analysis of fixation lengths examined the time spent on different visual components as a function of language groups and event types. In both language groups’ explorations, fixations were longer on P than on the other AoI. Fixation durations with cartoon scenes can be summarized as follows:
$$ \mathrm{Duration}\ \mathrm{of}\ \mathrm{fixations}\ \mathrm{in}\ \mathrm{cartoons}:\mathrm{P}>\mathrm{P}\pm \mathrm{M}=\mathrm{G}=\mathrm{S} $$
Specific comparisons showed that fixations were overall longer on Path areas than on Manner areas in both languages (Pbroad vs. P ± M: F(1,36) = 6,645783, p = 0.013) and that the duration of fixations (whether on Manner or on Path areas) did not vary across language groups. Figure 18 shows the proportions of fixation times spent on P ± M and Pbroad areas with cartoons. Further analysis revealed no global effect of core-event-type, yet a significant impact of this factor on specific areas, particularly on fixations to both P ± M and Pbroad areas (F(2,72) = 16.96, p < 0.001; and F(2,72) = 21.00, p < 0.001, respectively). Overall, Manner fixations were longer with across items and Path fixations with down items.
Figure 18. Fixation lengths on P ± M and Pbroad AoI with different item types in cartoon scenes.
Although the analysis of the video scenes revealed no significant language effect with respect to fixation durations, a significant main effect of AoI was found (F(4,144) = 20.93, p < 0,001), as well as an interaction between language and AoI type (F(4,144) = 2.42, p = 0.05). More specifically, fixations were longer on Path (P), Manner (P ± M), and Goal (G) as compared to Source (S) areas, while durations were not significantly different for P ± M-, P-, and G-AoI. The results for the duration of fixations in the videos can be summarized as follows:
$$ \mathrm{Duration}\ \mathrm{of}\ \mathrm{fixations}\ \mathrm{in}\ \mathrm{the}\ \mathrm{videos}\;\mathrm{set}:\mathrm{P}=\mathrm{P}\pm \mathrm{M}=\mathrm{G}>\mathrm{S} $$
As shown in Figure 19, further analyses focusing on the length of fixations to the main Manner (P ± M) and Path areas (Pbroad) showed again that, overall in both language groups, fixations were longer on Path than on Manner areas (Pbroad vs. P ± M: F(1,36) = 19.41, p < 0.001). Furthermore, within each language, fixations lasted significantly longer on Path AoI than on Manner AoI during both French (F(1,18) = 12.10, p < 0.01) and English (F(1,18) = 7.65, p = 0.012) explorations. Finally, although the analysis revealed no significant effect of core-event-type, an effect of this factor was found in relation to specific AoI in that Manner fixations were longer with down items and Path fixations with up, out-of, and into events.
Figure 19. Fixation lengths on P ± M and Pbroad AoI with different item types in video scenes.
In sum, the duration of fixations to Path and Manner areas did not depend on language, but varied as a function of Path types in the targets. Overall, fixations lasted longer on Path than on Manner areas, especially with boundary crossing and upward motion events, while the longest Manner fixations occurred during the processing of across events in the cartoons and of down events in the video set. The data do not support the initial prediction according to which Manner fixations were expected to be longer for English than for French viewers.
Gazeplots. A descriptive analysis examined qualitatively how fixations were distributed, on-line, during participants’ visual exploration of events. As shown in Figures 20 and 21, differences across language groups were observed in the number, order (numbered gaze points), and duration (size of gaze points) of fixations. For example, for the same upward event (cartoon), French fixations were found to be ‘ballistic’, going back and forth from S to G areas several times, performing large amplitude saccades (Figure 20, example on the left) in several steps, as opposed to a more minimalist, sequential pattern traced by English viewers who followed the figure’s motion step by step, in a linear way (right).
Figure 20. Scene exploration in the production task – ‘climb/up’ event in the cartoon set: ballistic exploration by the French viewers (left) and linear exploration by the English viewers (right).
Figure 21. Scene exploration in the production task – ‘jump/out-of’ event in the video set: ballistic exploration by the French viewers (left) and linear exploration by the English viewers (right).
Figure 21 illustrates how French and English viewers allocated their attention through an ‘out-of’ (video) item. This is a spatial depiction of where participants fixated their gaze and how they navigated through the video stimulus revealing hotspots and the same gaze pattern distribution observed previously: a ‘ballistic’ way of processing by the French viewers characterized by great amplitude in the gaze saccades that drive fixations (left) and a rather linear processing of the same event by the English viewers with shorter saccades and less fixations during scanning (right).
3.3.2 Categorization tasks
In experiments 1 and 2, two additional AoI were defined: M-AoI corresponding to the Manner-congruent variant presented after the target video and P-AoI corresponding to the Path-congruent variant the participants were shown. All other fixations fell to a general area x that covered the rest of the (blank) screen display.
Numbers of fixations. Mixed ANOVA were conducted on raw numbers of fixations including genderFootnote 14 and language as across-subject factors and Path type, Manner type, AoI type, and categorization type as within-subject factors, once for the non-verbal task, once for the verbal task, and once to compare the two. First, the analysis revealed a main AoI effect, significant both within and across tasks (CatNV: F(4,144) = 372.51, p < 0.001; CatV: F(4,144) = 598.97, p < 0.001; across tasks: F(4,144) = 694.74, p < 0.001), and a Path-type effect, significant only in the non-verbal task (F(3,108 = 5.40, p < 0.01) and across tasks (F(3,108) = 5.50, p < 0.01), but no Manner type or language effect. However, the language factor was found to interact with the AoI factor in the verbal task (F(4,144) = 7.17, p < 0.0001) and across tasks (F(4,144) = 4.56, p = 0.001), as well as with the Manner-type factor in the non-verbal experiment (F(2,72) = 6.75, p < 0.01) and across tasks (F(2,72) = 7.50, p < 0.01). More specifically, overall participants fixated Path-congruent variants more frequently than Manner-congruent variants in the non-verbal experiment (P vs. M: F(1,36) = 37.25, p < 0.001), but not in the verbal one, during which English participants fixated more the Manner-congruent variants than the Path-congruent ones, and this is significantly more than the French viewers (Figure 22). With respect to the categorization-type factor, the analysis showed a significant interaction between categorization types and AoI types on the number of fixations to each specific AoI (task effect on M-AoI: F(1,36) = 18.50, p < 0.001; and on P-AoI: F(1,36) = 60.13, p < 0.001), in that there were overall significantly more fixations in the verbal task as opposed to the non-verbal one, suggesting the difficulty the viewers had in this task to make a choice between M- and P-congruent variants.
Figure 22. Mean fixation numbers on Manner- and Path-congruent areas by French and English viewers across categorization tasks.
Further analysis on specific item types showed no significant Manner effect, either within or across tasks, but a significant global effect of Path type in the non-verbal task (F(3,108) = 5.40, p < 0.01), as well as across tasks (F(3,108) = 5.50, p < 0.01). The analysis also revealed a significant AoI-type effect on each individual core-event-type in both tasks: in the non-verbal categorization (default-P: F(4,144) = 165.77, p < 0.001; vertical-P: F(4,144) = 284.96, p < 0.001; one-boundary-crossing-P: F(4,144) = 181.99, p < 0.001; two-boundary-P: F(4,144) = 149.11, p < 0.001) as well as in the verbal categorization (default-P: F(4,144) = 358.30, p < 0.001; on vertical-P: F(4,144) = 316.76, p < 0.001; on one-boundary-crossing-P: F(4,144) = 343.40, p < 0.001; on two-boundary-crossing-P: F(4,144) = 115.33, p < 0.001). More specifically, Path fixations were found to be more frequent with vertical (up, down) and one-boundary-crossing (into, out-of) events, while Manner fixations were more frequent with default (along) and double-boundary-crossing (across) events, in both tasks. However, further tests exploring how different groups allocated their attention with different core-event-types in the targets revealed no significant language effect.
Fixation lengths. Similar mixed ANOVA were conducted on fixations’ duration, showing no significant effects of gender, Path-, or Manner-item-type in either task; thus, these factors were discarded from the following discussion of the results. With respect to the AoI-type and categorization-type factor, the durations of the fixations were found to vary significantly depending on the variant involved both within and across tasks (in the non-verbal task: F(4,144) = 567.78, p < 0.001; in the verbal task: F(4,144) = 775.55, p < 0.001; and across tasks: F(4,144) = 1028.73, p < 0.001). In addition, the AoI-type factor interacted with the language factor, again within and across tasks (marginally in the CatNV: F(4,144) = 2.38, p = 0.05; significant in the CatV: F(4,144) = 9.88, p < 0.0001; and across tasks: F(4,144) = 7.91, p < 0.0001), in that in both tasks, fixations were overall longer for Path-congruent areas than for Manner-congruent areas (P vs. M in CatNV: F(1,36) = 9.11, p < 0.01; and in CatV F(1,36) = 15.95, p < 0.001, respectively), with French viewers spending more time exploring P-congruent video variants in both categorization tasks (experiments 1 and 2), as illustrated in Figure 23.
Figure 23. Mean fixation lengths (msec) on M- and P-congruent areas by French and English viewers across categorization tasks.
Gazeplots. A descriptive analysis examined qualitatively how fixations were distributed on-line during participants’ visual exploration during the exploration of target videos in the categorization tasks. As shown in Figure 24, the same differences observed in the production task (experiment 2) were also observed in the exploration of the target events during experiments 1 and 2. For example, for the same out-of event, French viewers fixated the scene in a ‘ballistic’ way, going back and forth, from S to G areas several times, as opposed to the linear pattern of the English fixations that followed the figure’s motion step by step.
Figure 24. Target scene exploration during non-verbal categorization: ballistic exploration by the French viewers (left) and linear exploration by the English viewers (right).
4. General discussion
The current study investigated how speakers from two typologically different languages, English and French, conceptualize and represent voluntary motion events in tasks that involved language to different degrees (non-verbal categorization, verbal categorization, production) and in varied event and scene types. Two main questions were addressed: (i) whether the differences of these two contrasted languages constrain participants’ verbal performance in specific ways according to different contexts (varied event saliency and scene nature contexts) and (ii) whether cognitive influences (during attention allocation and decision-making) arise both when language is and is not explicitly involved. A first null hypothesis predicted no major language effects of any kind, whereas a second typological hypothesis predicted language effects to various degrees (either in all measures or at least during verbalization). Overall, the four sets of analysis (similarity judgment data, RT data, production data, and eye-movement data) offer the possibility for a deep investigation and a fine-grained account of the impact language may have on non-verbal processing.
4.1. Effects with maximal involvement of language
With respect to the production data, based on two different scene settings (video clips and animated cartoons) involving different types of voluntary motion events (boundary crossing, vertical motion events), participants’ verbal descriptions and their on-line visual strategies during preparation for verbalization were examined in order to determine whether the verbal and non-verbal behavior of speakers differs as a function of their linguistic background and, if so, with which scene contexts and item types. As expected by the typological approach, speakers’ verbalizations differed as a function of their language type. Responses were overall semantically denser in English than in French, and this difference was much more striking with boundary-crossing events than with other item types. More specifically, English speakers systematically combined Manner (encoded in the verb) and Path (in other devices) following the typical Satellite-framed pattern of their language (PM conflation), while French speakers followed the typical verb-framed pattern, focusing mostly on Path-alone (lexicalized in the verb) constructions, notwithstanding frequent PM combinations in some contexts (e.g., with upward motion in cartoons; with single-boundary-crossing events in videos involving a change of state). The results concerning response architecture showed that TS responses were predominant across groups with the cartoon set, but not with the video set. Video scenes elicited the expression of both Manner and Path components, thus inviting French speakers, for whom Manner is normally optional, to produce TC utterances (typically with the addition of gerunds) or LC utterances (typically distributing information in coordinated or juxtaposed clauses). Additional language-specific strategies emerged when scenes involved highly salient components that are otherwise downplayed, such as Manner for French. For example, a video showing a figure riding a bicycle or riding a scooter uphill made Manner much more salient than is typically perceived by French speakers. These participants therefore paid more attention to this component than they would do habitually, expressing Path in a main clause and Manner in the periphery using complex structures involving a dependent element (TC). These data support both the Manner salience and Path salience hypotheses, additionally underlying the need to combine lexicalization and event integration theories, in the Talmyan sense, when studying language asymmetries of this type. Indeed, Manner was found to be more salient and central in English and Path more salient in French, but the way these components were combined or distributed (combined with the use of other peripheral devices or lexicalized in separate clauses) reveals the bigger picture of how language constrains encoding patterns across different dimensions. For example, English invites the expression of both Manner and Path within compact and dense constructions. In comparison, when French speakers want to express Manner in addition to Path, they often have to do it periphrastically adopting complex or loose constructions.
The eye-tracking data provided additional information concerning the on-line processing of these events as participants were preparing their verbalizations. As predicted by the typological hypothesis, the number of fixations showed that, depending on the language group, spatial information is not only encoded differently, but also partially filtered visually in different ways. The frequency of fixations, but not their duration, differed across groups as a function of language background. In line with predictions based on Talmy (Reference Talmy2000) and Ibarretxe-Antuñano (Reference Ibarretxe-Antuñano, Guo, Lieven, Budwig, Ervin-Tripp, Nakamura and Özçalışkan2009), this language effect stemmed from a difference in the Path salience of the events and not from salience in Manner (cf. Slobin, Reference Slobin, Hickmann and Robert2006). In addition, although both groups fixated Path more than Manner (especially in the absence of intrinsic boundaries), French viewers fixated more frequently Path areas than the English group, especially with the cartoon scenes. Surprisingly, the duration of fixations did not depend on language, but rather on the motion components that were visually displayed, and on the specific Paths involved in the stimuli: fixations were significantly longer on Path areas, particularly with vertical motion (up, down events), and this difference was again even more striking in the cartoon set. Finally, in both languages, gazeplots also showed a general preference for Path over Manner fixations during participants’ exploration of events, while also providing further information about the on-line distribution of attention allocation during the visual scanning of motion: ballistic fixations by the French group as compared to the linear exploration strategy of the English group.
4.2. Effects with minimal or no involvement of language
The analysis of the two categorization tasks (experiments 1 and 2) took into account the degree of involvement of language (minimal verbal input involvement with the presented audio sentences in the verbal categorization task – experiment 2 and no involvement of language in either the input or the output of the non-verbal categorization task – experiment 1). Overall, both the off-line and on-line data support the Path salience hypothesis according to which Path, as the core (framing) event, attracts the attention of all groups but constrains even more the mechanism of perceptual processing when the viewers come from a Path-oriented (verb-framed) language such as French. The responses to the experimental items showed indeed that, when categorizing events, participants had a general preference for the framing event (the core/universal component: Path) and, as expected, this criterion was the main categorization criterion across groups. However, with respect to the Manner-congruent responses, the results show a clear language effect in that when Manner-congruent variants are selected, they are selected twice as much time as French by the English participants in the verbal task, and this preference is even more striking with items involving boundary-crossing contexts and instruments. This language effect was clear in the similarity judgment measure of the verbal task but not significant in the RT measure.
More specifically, given the systematic encoding of both Manner and Path in (satellite-framed) English, it was expected that the speakers of this language would take more time to make their (P- vs. M-congruency) decisions, as opposed to French, who were expected to focus mostly on Path-congruency and thus take less time to decide which component is most important to them. Despite the general tendency in the similarity judgments to select P-congruency over Manner-congruency across groups (in line with previous observations by Ji, Reference Ji2017) and a significant task effect (categorization-type factor), such that participants took longer to respond in the verbal task than in the non-verbal task, no language effect was found in the time spent from stimulus onset until categorization. However, depending on the specific Manner or Path information involved in the stimuli, participants spent more or less time processing incoming information before making their categorical choices, but again they did not differ in this respect across language groups. Specific item type analyses revealed that RTs were longer with items involving instruments and one-boundary crossing, as opposed to simple no instrument, default for humans, displacements (running/jumping or walking), and double-boundary crossing, respectively.
The analysis of the eye-fixations during similarity judgments showed that motion components attracted the visual attention of participants to different degrees and that the number of fixations to specific AoI depended not only on the type of the task (verbal/non-verbal) but also on their language background. Overall participants fixated Path more frequently than Manner variants in the non-verbal task, but not in the verbal one, during which English participants fixated more the Manner-congruent variants than the Path-congruent ones, and this is significantly more than the French viewers. With respect to the global categorization-type factor, the analysis showed a significant interaction between categorization and AoI types on the number of fixations in that there were significantly more Manner and more Path fixations in the verbal task, as opposed to the non-verbal one, suggesting the difficulty the viewers had in this task to make a choice. Further analysis on specific item types showed no significant Manner-type effect either within or across tasks, but a significant effect of Path type in the non-verbal categorization task as well as across tasks. More specifically, Path fixations were more frequent with vertical (up, down) and one-boundary-crossing (into, out-of) events, while Manner fixations were more frequent with default (along) and double-boundary-crossing events, in both tasks. However, further tests exploring how different groups allocated their attention with different event types in the targets revealed no significant language effects.
With respect to fixation lengths, the durations of the fixations were found to vary significantly depending on the variant involved, both within and across tasks. More specifically, in both tasks, fixations were overall longer for Path-congruent areas than for Manner-congruent areas, especially for the French viewers who spent more time exploring the two video variants, but also remained mainly focused on the P-congruent ones across tasks.
Finally, the gazeplots revealed once again a ‘ballistic’ way of processing visual information by French viewers as opposed to the more linear pattern of English viewers, who tended to follow the figure’s progression step by step. This observation most probably relates to the linguistic properties of the two languages and their implications not only for the expression of spatio-temporal boundaries but also for the visual attention patterns the viewers adopt, more generally. For example, the ballistic eye exploration of French viewers could be explained in part by the optionality of Manner in this language. That is, French participants had to decide for a given motion event whether it was Manner of motion worthwhile to be selected or Path. To make their decision, French viewers first inspected the Path (core component/essential for verbal production) but then went back to check the motion again, even when verbal encoding was not expected in the task.
Apart from the differences in lexicalization patterns, the variation in gaze patterns could also stem from the specificities of these two languages in terms of aspectual features (cf. Aske, Reference Aske, Hall, Meacham and Shapiro1989; Demagny, Reference Demagny2015; Riegel et al., Reference Riegel, Pellat and Rioul1999). For example, in English, the systematic encoding of both Manner (in the verb) and Path (in other devices) invites speakers to focus their visual attention on both spatial components. In addition, the existence of a grammaticalized progressive marker in English (but not in French) enables them to express explicitly ongoing events and thus focus on the progressive development of a displacement. As a result, English participants tend to adopt a linear strategy whereby a motion event is viewed as a sequence of successive points. In comparison, French participants typically focused on Paths, especially the median and final parts of Path (systematically lexicalized in verbs when verbal encoding is at play, downplaying Manner or not expressing this component at all), which explains to some extent their use of ballistic exploration strategies even when verbal encoding is not at play.
Finally, this preference for ‘linear’ versus ‘ballistic’ event exploration may stem from other, psychophysical parameters, such as the general tendency of humans (but also of some nonhuman primates) to explore events following a more or less ‘focal’ versus ‘ambient’ visual strategy, and more specifically to be interested in Endpoints and time-to-contact (TTC) estimations, especially in complex situations of moving objects and agents (for an extended review on the processes involved during TTC estimation and ambient/focal visual exploration strategies, see Bennett et al. (Reference Bennett, Baures, Hecht and Benguigui2010), DeLucia and Lidell (Reference DeLucia and Lidell1998), Tresilian (Reference Tresilian1995), Helo et al. (Reference Helo, Rämä, Pannasch and Meary2016), and Pannasch et al. (Reference Pannasch, Schulz and Velichkovsky2011), among others).Footnote 15 The qualitative difference observed in the gazeplot data may stem from the fact that French and English viewers are not equally sensitive to the bigger picture/the aim of the event, or at least do not make the same effort to estimate TTC. French viewers have a greater tendency for extrapolation and scan events following an ambient strategy that involves saccades with larger amplitudes and fixations that help them estimate the distance and the velocity of moving figures, from initial (Source) to final (Goal/Endpoint) parts, back and forth several times, most probably driven by the Endpoint/contact- or boundary-crossing point of the event, which seems more salient to them than to English viewers.
4.3. Variability during event processing and theoretical implications
The results only partially support the initial predictions (e.g., those from the linguistic/typological approach). Despite some general language effects, important variations were observed depending on the types of scene sets, event types, and measures. For example, in the production data, language effects were less strong with videos and with events involving intrinsic boundaries. In the on-line data, the frequency of fixations and the gazeplots suggest language effects that stem from the degrees to which participants focus on Path (and its subcomponents) across languages (but not on Manner). Additionally, and contrary to the initial expectations, the results of fixation lengths and RTs during categorization suggest that the timing of cognitive processing during visual perception and decision-making is language-independent.
Several factors could account for the complex patterns observed in participants’ verbalizations in comparison with their visual attention and decision-making. First, general cognitive factors may account for some of the similarities that were found across the two language groups. In particular, notwithstanding differences in perceptual focus across languages, both groups overall encoded Path in their utterances and paid much visual attention to Path (Pbroad AoI) as compared to areas that also included Manner (P ± M).Footnote 16 This pattern was not expected by any version of the typological hypothesis, which predicted generally more visual attention to Path by the French group and either more visual attention to Manner or equal attention to Path and Manner by the English group. This result may not be surprising if we assume that Path is the most basic semantic and cognitive component of motion, determining for example details about the changes of location of protagonists that are essential to construe the event perceptually and to reconstruct it in discourse maintaining the framing event as the core element of encoding (see also Talmy, Reference Talmy2000, about the universal aspects of Path).
Second, language-specific factors invited speakers to pay attention to different components of motion, showing overall a clearer focus on Path as compared to Manner in the French group than in the English group. Given the properties of English and French, all versions of the typological hypothesis predict that the most accessible components should differ across languages. Furthermore, at least one version of this hypothesis predicts that such language-specific factors should also (at least partially) affect speakers’ attention allocation. This language effect was clearer in the quantitative analyses of fixation counts that showed the different degrees to which viewers allocated their attention to Path. With respect to similarity judgments, the language effect stemmed from the different degree of Manner salience, which led the English participants to choose this criterion twice as much as the French ones.
The results of this study also indicate the impact of a third constraint related to perceptual factors. In particular, subjects’ attention allocation differed to some extent across the two sets of scenes, as well as across item types within each set (e.g., into/out-of for videos, up/down for cartoons). These differences raise some questions concerning the perceptual features of such visual stimuli. The video set provided highly controlled natural scenes of human voluntary displacements in fixed settings (interior/exterior doors, hill, road), while the cartoon set provided more varied situations of voluntary motion involving different types of figures (humans and animals) in diverse settings (e.g., house, plant, tree, lake, road, river), all contextualized with elements motivating the aim of the motion event (e.g., climbing up a table/tree to get food). Thus, cartoon scenes invited speakers to organize their responses in the form of a short narrative, as opposed to videos that elicited rather short responses merely describing main spatial components (Manner/Path). As a result, when planning their verbalizations but also when attending to specific components in these scenes for the purposes of categorization, speakers/viewers adopted different perceptual strategies: more ambient by the French viewers and more focal by the English viewers – a difference that was more striking in the cartoon set than in the video set (for a similar discussion, see also Soroli et al., Reference Soroli, Hickmann, Hendriks, Aurnague and Stosic2019).
In summary, the findings show a complex interrelationship between language, perception, and action (see also Spivey, Reference Spivey2023 for a recent discussion). In some cases, language knowledge clearly guided visual processing and consequently – at least in strongly verbal contexts – decision-making (action decisions); in others, language experience only partially influenced cognitive processing. This work suggests that cognitive processing (perception, reasoning, decision-making), including language processing, depends in part on general genetic/universal determinants (as reflected in some systematic language-independent choices – e.g., overall preference for the expression or the selection of the core spatial component (Path), compact TS encodings) and in part on acquired/epigenetic learning mechanisms that arise from our interactions with the world (e.g., experience with specific perceptual features, linguistic properties, action affordances).
Such an interactive perspective is in line with current dynamical system conceptions of language that consider it as a complex and open interactive network in which variability is an inherent property (e.g., De Bot et al., Reference De Bot, Lowie and Verspoor2007; Hotton & Yoshimi, Reference Hotton and Yoshimi2011; Larsen-Freeman & Cameron, Reference Larsen-Freeman and Cameron2008). More specifically, in the domain of spatial language and cognition, the present work can contribute to such dynamical accounts by defining the necessary scientific concepts that capture the specific semantic and syntactic properties of the involved meaningful units (e.g., focus to specific spatial components), the general constraints of the system in terms of lexical/grammatical distribution (locus), as well as the laws of their combinatorial assemblies (main architectural patterns) in order to better understand the individual interactions at the perceptual (visual processing) and motor action (decision-making) levels. Developing further a formalized dynamical approach to language–thought interactions that takes into account the relative weight of perceptual, linguistic, and action mechanisms involved in spatial cognition may improve current integrated accounts about human behavior.
From the above, it is obvious that future research on the constraints involved in the conceptualization and representation of motion must further examine variation across and within languages or language types as a function of several other extralinguistic factors. General/cognitive factors as well as typological and perceptual factors (related to event features, scene settings, etc.) all seem to play an important role not only at the formulation level but also at the level of our internal representations.
4.4. Toward a non-modular interactive account
During the past decades, the general paradigm of cognitive science has been switching from (linear or cascade) modular conceptions of cognition toward models that integrate body/mind, language, and environment interactions, thus allowing progressively for contextual (top-down) influences to become operative the moment they are made available in thought through the sensory input (e.g., McClelland, Reference McClelland, Inui and McClelland1996; Ryskin & Fang, Reference Ryskin, Fang, Federmeier and Sahakyan2021; Spivey, Reference Spivey2007). In this work, the aim was to focus on voluntary motion event processing as perceived in the form of visual and auditory sensory input, and let speakers/viewers from different language backgrounds (English- and French-speaking) (re)act through active/overt (e.g., button selection, verbal production) and covert inferences (e.g., eye-movements, RTs). By manipulating the visual contexts (the degree of saliency of specific spatial components, the nature of human/animal body affordances, and the naturalism of event execution) and by introducing controlled speech streams for explicit verbal bias, when necessary, the effects of visual perception and language to overt behavior (verbal encodings, similarity decisions) and sometimes even in covert behavior (attention allocation patterns) emerged. The focus was on events that involve representations of spatial relations, e.g., Manner, Path, Goal/Endpoints, Source, etc. through specific semantic focus in construal selection, distributed in meaningful units that take the form of verbs, adverbs, prefixes, particles, prepositional phrases, etc. (locus), and further organized into semantico-syntactic constructions – architectural chains of form, meaning, and function (cf. Talmy, Reference Talmy and Hampe2005).
The integrated approach supported by the findings, and schematically presented in Figure 25, aims to describe possible language and cognitive interactions in the domain of motion events. It is an illustration inspired by previous situated frameworks (such as the action perception theory by Pulvermüller (Reference Pulvermüller2013), the complex and dynamic systems theory by De Bot (Reference De Bot, Ortega and Han2017) among others) that identify processes and active interactions between the perceptual, action, and language domains. Such a framework has the advantage to allow, for example, spatial semantic mechanisms (e.g., spatial component selection, conflation) to be effective within the language strand but also to be influenced, in an interactive way, by other processing components related to perceptual or action generation mechanisms (e.g., the number and complexity of the sensory properties one has to process/extract, the saliency of the involved components, the naturalistic nature of a scene, the demands of the task).
Figure 25. A dynamic framework of the language–body/mind interaction.
The schematic diagram proposed in Figure 25 illustrates a dynamic account of event processing, which takes into account different levels of variation. In this dynamic framework, the cognitive system is viewed as able to reshape so that it is temporarily dedicated to one type of task or another, depending on the available context. For example, the system can function mostly as a sensorimotor processing system by boosting the coupling of perception and action processes leaving the coupling with the language processor partially or completely inactive (inactivation is marked in gray), for instance, in cases when language is not explicitly involved or necessary (e.g., simple reflex sensorimotor actions such as removing our hand from a heating surface, juggling to grasp a slippery object). In such cases, the system is expected to carry out an action (e.g., juggling to grasp a slippery bar of soap in the shower, as described by Gibbs & Van Orden, Reference Gibbs and Van Orden2003). In such contexts, the precise movements are task-specific and active (e.g., bringing the soap back under control), not necessarily anticipated before they are enacted. A covert reaction or a movement (e.g., a rapid saccadic change, juggling) emerges because the situation to be controlled changes. However, in intentional contexts, when the situation changes rapidly and involves complex events that combine core and co-event information as in the case of event categorization tasks described in the present study, language gets back to the game and acts as a support, especially for ambiguous/not sufficiently salient situations when viewers are expected to compare subtle differences, e.g., between default and non-salient Manners of motion without instrument (walking vs. running), and make a decision (similarity judgment). In this sense, a rapidly changing situation, as the one exposed the participants of this study in the categorization tasks, creates the intention to adapt the non-verbal behavior by choosing unique event-specific responses – an adaptation that becomes trickier in complex/non-salient situations and when verbal input is not directly available. In other words, special circumstances (perceptual salience, knowledge of affordances, linguistic knowledge, etc.) vary in their degree of involvement and lead humans to unique inferences, allowing their system to dynamically and flexibly adjust to sensory-, task-, and/or language-specific requirements during action planning.
5. Conclusion
The present paper combined off-line and on-line measures across two typologically different languages, English and French (satellite- vs. verb-framed). The aim was to explore the language–thought relationship in two ways: (a) to test various hypotheses concerning the presence or absence of language effects on how speakers conceptualize motion events in verbal and non-verbal behavior and (b) to identify how different situations related to event and scene properties contribute to this process. The findings show clear differences in speakers’ linguistic representations that follow directly from the typological properties of their language but also some partial language effects on non-verbal measures (categorization choices, fixation counts) when salient motion-relevant information was involved during event processing. The results, discussed in light of cognitive psychology and linguistics, support a moderate version of the relativity hypothesis and highlight the need to formulate precise and subtle views of the relationship between language use and on-line visual processing that take into account cognitive and typological factors as well as the perceptual properties of events.
More generally, the findings do not support a modular approach but rather an interactive and integrated (body/mind–language–environment) approach to the Langue-Cognition debate. In such a framework (similar to what has been described recently by other psycholinguists, acquisitionists, and neuroscientists – cf. De Bot, Reference De Bot, Ortega and Han2017; Pulvermüller, Reference Pulvermüller2018; Spivey, Reference Spivey2023), interactions play a central role – represented here by context effects revealing that contextual information (e.g., the demands of the task, the degree of salience of certain features, speakers’ linguistic knowledge) may modulate not only our verbal behavior but also, in some cases, our actions and covert inferences. Context effects are reported in the findings of this study by taking into account different types of salience variables: spatial components involving different core events (events without boundary crossing, with one-boundary crossing, with two-boundary crossings), different co-events (default-Manners, Manners with/without instruments), different scene types (artificial/cartoon-like vs. natural/video depictions), affordances (involving human vs. animal motion features), and language involvement (language involved massively during the production task, partially during the verbal categorization task, or not at all during the non-verbal task).
The interactions reported suggest that the subsystems of perception, identified by physiologists and psychologists in the 80s and 90s, are not as modular as once thought (Fodor, Reference Fodor1983; Karmiloff-Smith, Reference Karmiloff-Smith1992; Marr & Vaina, Reference Marr and Vaina1982). Feedback and crosstalk connections with the sensorimotor/action system and the language system are or have to be added to traditional modular ‘box-and-arrow’ models to accommodate such findings, transforming the classic modular frameworks into something befitting an interactive and integrated network that covers findings from both action perception studies (e.g., Petro et al., Reference Petro, Paton and Muckli2017; Shebani & Pulvermüller, Reference Shebani and Pulvermüller2013; Spivey, Reference Spivey2007) and cognitive experimental linguistics (e.g., Boroditsky, Reference Boroditsky, Spivey, McRae and Joanisse2012; Flecken et al., Reference Flecken, Athanasopoulos, Kuipers and Thierry2015; Soroli et al., Reference Soroli, Hickmann, Hendriks, Aurnague and Stosic2019). To conclude, an account of interactions (within and across domains of processing) is necessary in a theory about human functions and event processing. Spatial cognition is no exception. Human cognition, in the spatial/motion domain, should be seen as a highly interactive process that involves several factors of influence including language processing.
Data availability statement
The lists of stimuli, together with the anonymized quantitative summaries of the data reported in this article, can be found at https://osf.io/2hdxg/?view_only=9408ab7e47844ed2b302ef5eedc621b3. The video and cartoon stimulus sets are available upon request.
Acknowledgments
I express my gratitude to Maya Hickmann and Philippe Bonnet for their invaluable assistance and thoughtful discussions regarding earlier versions of this work. My gratitude extends to two anonymous reviewers whose insightful feedback significantly contributed to refining this article.
Funding statement
The research presented herein received partial support from the ANR-DFG Langacross Project under award number ANR-07-FRAL-0007. Lastly, I would like to acknowledge the support generously provided by the Academic Council of the University of Lille, the National Council of Universities, and the French Ministry of Higher Education, Research & Innovation through a PEDR (2019-2023) and a CRCT (2023-2024) grant.
Competing interest
The author declares none.
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