To what extent do language and/or culture affect the way we process and organize the information and experiences that make up our world? The work of Sapir, Whorf, and others sparked this famous debate at least a century ago, and these questions continue to interest academics across fields to this day (Whorf, 1956; Lucy and Shweder, 1979; Kay and Kempton, 1984; Vygotsky, 1987; Lupyan, 2012; Levelt, 2014).

Most investigations addressing this topic have been characterized as either descriptive, simply reporting interesting differences between two or more languages, or aiming to explain how observed disparities are associated with different cognitive processes (Zlatev and Blomberg, 2015). These two perspectives are also associated with weak and strong versions of the Sapir–Whorf hypothesis (language and thought are interrelated vs. language determines thought, Brown, 1976). Both hypotheses have been criticized for being trivial and non-informative (weak version) or theoretically and/or methodologically wrong (strong version) (Bloom and Keil, 2001).

Zlatev and Blomberg (2015) propose approaching each investigation according to whether the focus is on the structure of language or on its implementation (discourse). Traditional cognitive approaches focus on abstract structural aspects of language and search for innate universal features. On the other hand, linguistic relativism concentrates on how the phenomenon of categorical perception (CP, Harnad, 2005) is affected by different contextual factors, such as language and culture.

According to Lucy (1997), there are three “logical components” that are typically taken into account when studying linguistic relativity: (1) the distinction between language and thought, (2) the mechanisms explaining the instantiation of a possible influence, and (3) the identification of other factors involved in the phenomenon.

Regarding the first point, relativists often agree with a broad definition of thought, not just as a conscious reflective process (as understood in folk psychology) but also involving less aware, automatic processes, such as perception and categorization. Moreover, language and perception are not understood as isolated modules—as in classic cognitivism (Pylyshyn, 1999)—but are thought to interact with a myriad of processes. Thus, the role of verbal labels affecting perception and categorization is a key issue in contemporary approaches (Thierry, 2016). How basic cognitive processes are influenced by implicit recovery of linguistic (but also contextual and sociocultural information) is another key question, which involves points 2 and 3.

Therefore, the key notion leading the research on linguistic relativity is not whether minds are dependent on a given language but how verbal labels and categories interact with cognition across different contexts (Thierry, 2016; Zhong et al., 2017). Topics currently being studied include: cross-cultural comparisons (i.e., Boroditsky, 2001; Casasanto, 2008), the exploration of categorical effects under different interference conditions (i.e., Roberson and Davidoff, 2000; Gilbert et al., 2006; Winawer et al., 2007), and the time course of the effect, which informs whether perception or higher cognitive processes are involved (Mo et al., 2011; Clifford et al., 2012; He et al., 2014; Forder et al., 2017).

One line of research within this debate concerns the way in which different languages divide color space. The key question within this work is whether these varying linguistic representations affect performance on tasks that are seemingly non-linguistic. In other words, does the way in which a particular language categorizes colors affect the way its speakers think about and organize color in their minds, even in the absence of an explicitly linguistic task? One special case—that of the color blue—has been studied by researchers across a number of languages, including Greek (Androulaki et al., 2006; Athanasopoulos, 2009; Thierry et al., 2009), Italian (Bimler and Uusküla, 2014), Japanese (Athanasopoulos et al., 2010), Korean (Roberson et al., 2009), and Russian (Witthoft et al., 2003; Winawer et al., 2007). These languages share a common feature that distinguishes them from English: they divide the color blue into two distinct linguistic categories, one depicting lighter blues, and the other depicting darker blues. In the above studies, speakers of those languages were relatively better than English speakers at distinguishing between color samples along the blue color spectrum when the samples’ names came from different linguistic categories, even though the task did not require linguistic output.

This kind of implicit linguistic effect is explained by theories arguing that linguistic labels can aid in the discrimination of stimuli that are hard to categorize (Lupyan, 2012) thanks to a predicting coding process in which “every level of the hierarchically organized system that constitutes the brain works to predict the activity in the level below” (Lupyan and Clark, 2015, p. 279). In such a predictive framework, the brain’s function is to produce a percept that fits the best hypothesis regarding the state of the world that is being conceived (Lupyan and Clark, 2015). That is acquired through an interplay of top-down knowledge about the world and incoming bottom-up sensory information (Bar, 2003). In Lupyan’s view, labels work as hubs of perceptual, semantic and contextual information related to specific categories. Their function is to reduce prediction error by enhancing the perception of typical categorical features. Therefore, verbal labels can be elicited to foster predictability and support cognition.

Aiming to clarify this issue, several studies include a verbal interference condition. That is, they introduce a concurrent task demanding linguistic resources (e.g., remembering a string of digits). This interference is expected to disrupt categorical effects (advantage for the discrimination of stimuli pertaining to different categories) if linguistic processes are necessary for CP to occur. For instance, Winawer et al. (2007) showed that when an additional task requiring verbal memory was included, the categorical effects found for the Russian participants vanished, suggesting linguistic resources are used by Russian speakers in this seemingly non-linguistic color perception task. The authors also presented a spatial interference condition that did not alter categorical effects, further supporting the view that the a disruption of the CP advantages was in fact due to a disruption in linguistic processing and not to the heavier cognitive load imposed by any interference task.

In the current study, we compared two groups of speakers of the same language that employ different verbal labels for the same color. This comparison is interesting because, unlike previous studies where groups of speakers spoke different languages, differences between the current groups should be much subtler, and may reflect cultural variations that affect the frequency of use of such labels.

Similarly to the languages investigated in previous studies (Androulaki et al., 2006; Winawer et al., 2007), in some variants of Spanish, the color blue is associated with two different linguistic terms: dark blues are azul and light blues are celeste. However, the Spanish language presents an interesting case, in that different populations of Spanish speakers differ in the way they implement this distinction. Namely, in some South American countries such as Uruguay, the term celeste (light blue) is used on its own. By contrast, in Spain, the term “celeste” is used as part of a compound word, i.e., azul celeste, making celeste a subcategory within the larger category of azul, or (regular or dark) blue. The word (and color) celeste also carries significant cultural weight in Uruguay, given that it is found on national emblems and by extension, national sports team uniforms. A recent study conducted by our group confirmed the use of celeste as a separate basic color term (BCT) for light blues in Uruguay. Thirty healthy participants were given 2 min to write down as many color names as they could remember while keeping their eyes closed (Elicited List task: Corbett and Davies, 1997). Following Berlin and Kay’s (Berlin and Kay, 1969) work, one would predict that only 11 different color names would be elicited in more than 50% of the lists produced by participants. In this study, however, Uruguayan participants consistently produced 12 names, as they included celeste as its own color category. In fact, both azul and celeste were consistently found among the first BCTs reported by Uruguayans (Lillo et al., 2016).

For the current experiment, we tested Uruguayan as well as Spanish participants on a color discrimination task we designed using stimuli along the azul-celeste boundary. Since cultural as well as linguistic differences have been used to explain Whorfian effects across different populations, the Uruguay-Spain comparison is interesting because the two populations come from different cultures but use the same language and very similar color space partitions. That is, when asked to assign segments of the color spectrum to different color terms, Uruguayans and Spaniards coincide perfectly on all terms except for celeste: the space Uruguayans call “celeste” falls into the greater category of “azul” for Spaniards (Lillo et al., 2016). Given the presence of the 12th BCT for the Uruguayans, we hypothesized that this group would display a relatively stronger categorical advantage than Spaniards.

We conducted a mixed ANOVA with three within-subject factors (Distance × Interference × Category) and one between-subjects factor (country: Uruguay vs. Spain).

The current study supports the Whorfian notion that language can influence color perception and is unique in that we were able to show differences in categorical effects in two groups of participants who speak the same language. Specifically, we found that Uruguayans, who have distinct color terms for light and dark blue, were more sensitive to color boundaries than Spaniards, who use a single color term for dark blue and two different compound terms for light blue. We also observed that a less frequent non-BCT—azul celeste—yielded some categorical facilitation. In this study, while both groups presented categorical effects in RT, the effect was strongest for Uruguayans on the more difficult “near” trials. Furthermore, only the Uruguayans were significantly more accurate at cross-category comparisons.

In contrast to previous studies where the color categories employed by the two populations clearly distinguished between dark and light blues (e.g., Russian and American participants in Winawer et al., 2007), one of the compound terms for light blue used by Spaniards (azul celeste) contains the monolexemic term (celeste) used by Uruguayans. From Lillo et al. (2016), we know that Spaniards do not consider “celeste” or “azul celeste” as a 12th BCT, as Uruguayans do, which may explain the weaker categorical effects observed among Spaniards relative to Uruguayans. Furthermore, as mentioned above, “celeste” is particularly salient in Uruguayan Spanish for cultural reasons, and may therefore appear more frequently for this population. According to several authors, the degree of exposure to color categories correlates with the strength of categorical effects in color discrimination tasks (Witthoft et al., 2003; Thierry et al., 2009; Athanasopoulos et al., 2011). An interesting future study would be to test category effects with a monolexemic color term whose frequency of use differs between two populations that speak the same language.

Importantly, several studies have shown that categorical effects on perception can be elicited by newly learned categories (Zhou et al., 2010; Clifford et al., 2012). In Zhou et al. (2010), participants who learned two new categories depicting light and dark shades of blue showed a categorical advantage compared with a control group, suggesting that the introduction of a novel verbal label can affect CP.

In Winawer et al. (2007), verbal interference disrupted CP for Russian but not for English speakers, suggesting a key role of language in CP (Roberson and Davidoff, 2000; Gilbert et al., 2006; Winawer et al., 2007). The results of the present study suggest that category saliency may also be affected by cultural factors.

Although the effect did not reach significance, we also observed that verbal interference diminished the categorical effect in Uruguayans and increased it in Spaniards (see Figure 7), which suggests CP effects are affected by linguistic input. Interestingly, Spaniards showed greater CP during the verbal interference block, suggesting the recruitment of the verbal label “azul” was inhibited. As shown by the Stroop effect (Stroop, 1935), automatic elicitation of a verbal label can interfere with color discrimination. Arguably, the discrimination between stimuli representing dark and light blues would benefit from the inhibition of the verbal label “azul” linked to the Spaniards’ main blue category. Thus, further work is needed to clarify this issue. If replicated, it would be an unusual finding that has not been reported for English speakers in previous cross-cultural studies.

It should be noted that because part of our study was conducted in Barcelona, some of our Spanish participants also spoke Catalan, which uses “blau cel” as a term for light blue. We have not studied “blau cel” or Catalan speakers specifically, so we cannot say whether this term is more similar to any of the terms used by Spaniards in Spanish or by Uruguayans. In order to exclude this variable as a possible confound, we conducted an additional ANOVA comparing the subset of Catalan-speaking Spaniards (n = 18) to the non-Catalan-speaking Spaniards (n = 15) and found that groups did not differ on any of the variables or interactions of interest.

A recent interpretation of Whorfian effects (proposed more than 100 years ago by William James; James, 1890) is called the Label feedback hypothesis (Lupyan, 2008, 2012), which proposes that labels (i.e., words) are automatically recovered to solve difficult discrimination cases and are recruited unconsciously when an object is perceived in order to highlight characteristic features and thus assist in the categorization process.

Furthermore, recent studies have revealed that neural networks of color perception show strong connections between basic visual areas V1 and V4 and inferotemporal and nearby regions associated with categorization (Walsh, 1999; Roe et al., 2012; Gilbert and Li, 2013; Simanova et al., 2015; Winawer and Witthoft, 2015). Moreover, an fMRI study showed activation of language regions during color perception, supporting the notion of an interaction between higher level cognition and perceptual processes (Siok et al., 2009; Brouwer and Heeger, 2013).

In the present study, perceptual processes seemed to benefit from the words’ referential attributes, but the effect differed between Spanish-speaking groups. This suggests that the interplay between categorization and perception only partially depends on a particular language’s structure (Ozgen and Davies, 2002; Harnad, 2005; Lupyan et al., 2007; Collins and Olson, 2014).

An alternative interpretation is that perception could be driven by cultural—and not just linguistic—influences. In fact, cultural differences in speakers of the same language may even be the driving force behind the creation of different linguistic terms. The Emergence Hypothesis for BCTs (Kay and Maffi, 1999) proposes an explanation for how BCTs have evolved in different cultures. Kay and McDaniel (1978) suggest that derived categories are a fuzzy set of intersections among primary terms. According to this view, the emergence of a new category denoting a light shade of blue would be the result of the intersection between the blue and white categories, as Androulaki et al. (2006) proposed for Greek. Exactly why a language would add a new BCT is not clear. Casson (1997) proposed that a society’s technological development will increase the importance of color as a distinguishing property of objects. Paramei (2005) and Steels and Belpaeme (2005) agree that cultural and social factors are key in the development of color lexicons. Such constraints imply that color names map onto color appearances in a culturally modal pattern (Frumkina, 1999; Jameson, 2005) and, in certain languages, could emerge as culturally basic.

Probably the main debate in linguistic relativity is whether CP occurs early on (during stimulus perception; Notman et al., 2005; Lupyan, 2012) or at the time a response is given (affecting post-perceptual processes; e.g., Pinker, 1995; Li and Gleitman, 2002). This question has been investigated using ERP, with studies showing early (Fonteneau and Davidoff, 2007; Thierry et al., 2009; Clifford et al., 2010; Mo et al., 2011; Forder et al., 2017), post perceptual (Clifford et al., 2012; He et al., 2014; Witzel and Gegenfurtner, 2016) and both effects (Holmes et al., 2009). This suggests that a strictly linguistic theory of CP is at best incomplete.

One unexpected result in the current study was that Uruguayans were both most accurate and fastest at the spatial interference block, relative to the other two blocks. One possible interpretation for this is that unlike verbal interference, spatial interference had a minimal effect on performance on a task where verbal aspects were critical, and that the added challenge resulted in higher accuracy. This would not, however, explain why that interference block would result in better accuracy than the block with no interference. We do not have enough data to answer this question at the moment but will investigate it in future studies.

Another interesting but not totally unexpected finding was that overall, Uruguayans gave slower responses than Spaniards. As observed by previous investigators, this may reflect differences in groups’ experience as study participants (Witthoft et al., 2003; Winawer et al., 2007; Witzel and Gegenfurtner, 2015). In the present study, while both groups were recruited within university psychology departments, the Spanish group was generally more familiar with psychophysical experiments than the Uruguayan group. In order to ensure that categorical effects across groups were not related to overall RT, additional analyses were performed on the subset (50%) of Uruguayans with the fastest responses. Results confirmed the trends observed for the whole group.

To conclude, color terms (both monolexemic and compound) carry different degrees of enhanced frequency and saliency within a linguistic community, which in turn depend on social, cultural, and historical factors (see Berlin and Kay, 1969; Casson, 1997; Kay and Maffi, 1999; Paramei, 2005, but also see Saunders, 2000). The present work shows that these differences can lead to different CP effects across groups that speak the same language.

This study was carried out in accordance with the recommendations of University of the Republic and Autonomous University of Barcelona ethics committees with written informed consent from all subjects. All subjects gave written informed consent in accordance with the Declaration of Helsinki. The protocol was approved by the University of the Republic ethics committee.

AA and FG-P conceived the study which was designed with the collaboration of IR and AM. IR and FG-P carried out the experiments and the analyses were conducted by AA, IR, and FG-P. All the authors contributed to the writing of the article.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.