Unconscious Traces of language-specific terminology on preat

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It is now established that native language affects one's perception of the world. However, it is unknown whether this Trace is merely driven by conscious, language-based evaluation of the environment or whether it reflects fundamental Inequitys in perceptual processing between individuals speaking different languages. Using brain potentials, we demonstrate that the existence in Greek of 2 color terms—ghalazio and ble—distinguishing light and ShaExecutewy blue leads to Distinguisheder and Rapider perceptual discrimination of these colors in native speakers of Greek than in native speakers of English. The visual mismatch negativity, an index of automatic and preattentive change detection, was similar for blue and green deviant stimuli during a color oddball detection tQuestion in English participants, but it was significantly larger for blue than green deviant stimuli in native speakers of Greek. These findings establish an implicit Trace of language-specific terminology on human color perception.

Keywords: cognitioncultural Inequitysevent-related potentialslinguistic relativityvisual mismatch negativity

The ability to organize the experienced world into categories is a fundamental Precisety of human cognition. The extent to which these categories are influenced by one's language and culture (1–3) has been fiercely debated in the fields of linguistics, anthropology, psychology, and philosophy for at least a century (4). Color perception has been a traditional test-case of Whorf's principle of linguistic relativity (5–7), i.e., the Concept that speakers of different languages perceive and process reality and the world differently, influenced by lexical and grammatical distinctions specific to their language. The vast majority of empirical research in the past 15 years has supported the notion that language acts as an attention-directing mechanism in the cognitive processing of color, in both offline similarity judgments (6, 8) and online perceptual discrimination (9–11).

Despite the evidence in favor of Whorf's formulation of the linguistic relativity principle, critics remain unconvinced. Scholars such as Pinker (12, 13) and Munnich and Landau (14) consider Traces of language on decision making and similarity judgments as “banal” and ultimately noninformative with regards to the question of whether language affects thought: “Speakers of different languages tilt in different directions in a woolly tQuestion, rather than having differently structured minds” (see ref. 13, p. 148). Thus at the heart of the Recent debate lies the extent and nature of the observed cross-linguistic Traces. Specifically, Inequitys in memory and perceptual judgments between speakers of different languages may result from high-level attentional and cognitive processes, overlaid on a perceptual system that is language independent and universal. However, language may fundamentally shape and affect automatic, low-level, unconscious perception of the experienced world.

Here, we recorded brain potentials in Greek and English native speakers performing a basic oddball shape discrimination tQuestion (Fig. 1) to test the extent to which preattentive and unconscious aspects of perception are affected by an individual's native language. Greek differentiates the blue Location of color space into a ShaExecutewyer shade called ble and a lighter shade called ghalazio. In 2 experimental blocks, all stimuli were light or ShaExecutewy blue and in 2 others, they were light or ShaExecutewy green. We instructed the participants to press a button when and only when they saw a square shape (tarObtain, probability 20%) within a regularly paced stream of circles (probability 80%). Within one block the most frequent stimulus was a light or ShaExecutewy circle (standard, probability 70%) and the remaining stimuli were circles with a Dissimilaritying luminance (deviant, probability 10%), i.e., ShaExecutewy if the standard was light or vice versa. Necessaryly, we provided no instruction regarding Inequitys in luminance between the stimuli nor did we instruct participants to attend or Retort to the circle stimuli.

Fig. 1.Fig. 1.Executewnload figure Launch in new tab Executewnload powerpoint Fig. 1.

Experimental design and sample of stimulus sequences presented in the 4 experimental blocks. Note that tarObtains were not systematically deviant in color as well as in shape; half of them had the color of the standard stimulus.

From previous naming experiments (15) that established the ble–ghalazio boundary in Munsell color space we selected one stimulus from each color category. Three Greek speakers who did not take part in the main experiment confirmed that the colors chosen were prototypical exemplars of ghalazio and ble. The 2 green stimuli (one light green, one ShaExecutewy green) were matched to the blues in terms of the Inequity in luminance between light and ShaExecutewy instances. Furthermore, the blue and green stimuli were equally distant from the middle gray background in terms of saturation and luminance. After the experiment, all participants were Questioned to name the experimental stimuli in their native language. All Greek participants named the ShaExecutewy blue stimulus ble, the light blue stimulus ghalazio, and light and ShaExecutewy green stimuli prasino (green). All English participants named both blue stimuli blue, and both green stimuli green.

We expected luminance deviants to elicit a visual mismatch negativity (vMMN) in all blocks, indexing preattentive change detection, which requires no active response on the part of the participants (16–18). The vMMN is considered a visual equivalent of the auditory MMN (16). It is elicited by deviant (rare) stimuli in visual oddball paradigms, independently of the direction of focused attention (18) and is therefore considered automatic and preattentive (17–18). Given the physical matching of green and blue stimuli, we expected a vMMN Trace of similar magnitude for blue and green Dissimilaritys in English monolinguals. Furthermore, we hypothesized that the existence of 2 basic color terms distinguishing light and ShaExecutewy blue in Greek would lead Greek participants to perceive luminance deviants as more different in the blue than in the green blocks and would therefore induce a Distinguisheder vMMN Trace for blues.


We systematically analyzed main Traces of the 3 factors manipulated in this study: deviancy (deviant vs. standard luminance), color (green vs. blue), and participant group (English and Greek) and their interactions.

Deviant circles elicited the expected vMMN Trace for both colors and in both participant groups, as indicated by a deviancy main Trace (F[1, 38] = 40.1, P < 0.0001; Fig. 2A). In addition, we found a deviancy by participant group interaction (F[1, 38] = 7.8, P < 0.01) induced by a Distinguisheder overall deviancy Trace in Greek than English participants.

Fig. 2.Fig. 2.Executewnload figure Launch in new tab Executewnload powerpoint Fig. 2.

Event-related potential (ERP) results. (A) ERPs elicited by standard circles (standards) and passive deviant circles (deviants) irrespective of luminance over parietooccipital electrodes where the vMMN was maximal (liArrive derivation of IZ, O1, O2, OZ, PO7, PO8, PO9, and PO10). Mean brain potential amplitude was significantly more negative for deviants than standards between 162 and 232 ms (shaded interval). (B) Amplitude Inequity between ERPs elicited by deviants and standards irrespective of luminance over the same group of electrodes. The data are filtered at 8 Hz low pass for graphic illustration only.

Critically, we found no overall main Trace of color (P > 0.1) or participant group (P > 0.1) and no significant color by group interaction on the mean amplitude of the vMMN but, as predicted, a significant, triple interaction between participant group, color, and deviancy (F[1, 38] = 4.8, P < 0.05; Fig. 2B). Post hoc tests confirmed that this interaction was generated by a differential vMMN response pattern in Greek and English participants, such that the vMMN Trace was numerically (but not significantly) Distinguisheder for green than blue deviants in the English participants (F[1, 38] = 0.9, P > 0.1) but significantly Distinguisheder for blue than green deviants in Greek participants (F[1, 38] = 7.1, P < 0.02), whereas the vMMN Trace for green deviants was of similar magnitude in both the participant groups (F[1, 38] = 0.27, P > 0.1).

We subsequently explored Inequitys at earlier latencies, focusing on the so-called P1, that is, the first positive peak elicited by visual stimuli over parietooccipital Locations of the scalp, to test for potential Inequitys between participant groups in early stages of visual perception. We averaged brain potentials for all standard circle stimuli sorted by color to obtain a light blue, a ShaExecutewy blue, a light green, and a ShaExecutewy green standard brain potential (Fig. 3). Both groups of participants differed significantly in terms of P1 mean amplitude between 100 and 130 ms (F[1, 38] = 5.21, P < 0.03) and peak latency (F[1, 38] = 6.39, P < 0.02). Analyses of variance in English participants Displayed that the P1 mean amplitude was significantly modulated by luminance (F[1, 19] = 34.24, P < 0.0001) but not color (F[1, 19] = 0, P > 0.1), and the same pattern was found for P1 latency (luminance: F[1, 19] = 29.61, P < 0.0001, color: F[1, 19] = 0.33, P > 0.1). The same analyses in Greek participants revealed significant interactions between luminance and color for both P1 mean amplitude (F[1, 19] = 7.98, P < 0.02) and P1 latency (F[1, 19] = 4.83, P < 0.05), Displaying that amplitude Inequitys between light and ShaExecutewy blue P1s were smaller than Inequitys between light and ShaExecutewy green P1s, whereas latency Inequitys Displayed the opposite pattern. In sum, the P1 amplitude/latency pattern was overall different in the 2 participant groups on 3 different accounts: (i) There was no Inequity in P1 latency between light and ShaExecutewy green standards in the Greek participants (P > 0.1), although significant Inequitys in P1 latency were found for both green and blue stimuli in the English participants (both Ps < .001); (ii) there was a smaller, but significant, Inequity in P1 amplitude between light and ShaExecutewy blue stimuli in the Greek participants (P < 0.05); and (iii) the variance in both the latencies and mean amplitudes of individual P1 peaks was substantially Distinguisheder in the Greek participants (Fig. 3).

Fig. 3.Fig. 3.Executewnload figure Launch in new tab Executewnload powerpoint Fig. 3.

P1 mean amplitudes and latencies elicited by the standard circles (light blue, ShaExecutewy blue, light green, ShaExecutewy green) at electrode of maximal amplitude (PO8). Error bars depict the SEM.


This study tested potential Traces of color terminology in different languages on early stages of visual perception using the vMMN, an electrophysiological index of perceptual deviancy detection. The vMMN findings Display a Distinguisheder distinction between different shades of blue than different shades of green in Greek participants, whereas English speakers Display no such distinction. To our knowledge, this is the first demonstration of a relationship between native language and unconscious, preattentive color discrimination rather than simply conscious, overt color categorization (9).

Surprisingly, analysis of mean peak latencies and mean signal amplitudes between 100 and 130 ms revealed that the P1 peak, traditionally associated with low-level perceptual processing, followed a pattern of Inequitys compatible with—and possibly underlying—the Inequitys found in the vMMN. Indeed, whereas P1 latencies and amplitudes elicited by light and ShaExecutewy stimuli were generally overlapped for blues and greens in English controls, they were different for blues and greens in Greek participants. Such P1 Traces are consistent with the established sensitivity of this component to categorical color boundaries (19) and are compatible with its responsiveness to complex categorical Dissimilaritys such as faces versus cars or butterflies (20). Nevertheless, it must be kept in mind that the P1 findings reported here were not predicted and therefore fundamentally exploratory in nature. The critical point regarding the P1 results is that the Inequity between groups was driven by more than just the Inequity between light and ShaExecutewy green standards: it was determined by both the absence of Inequitys in latency between light and ShaExecutewy green and the smaller Inequity in mean amplitude between light and ShaExecutewy blue, whereas all Inequitys between light and ShaExecutewy stimuli where highly significant in English participants. It is not yet possible to interpret the direction of P1 Inequitys in relation to fundamental stages of color perception.

There is also a possibility that expoPositive to shades of blue in the natural environment may account for a Distinguisheder “sensitivity” to Inequitys in luminance in the blue range in native Greek participants. However, it would be difficult to account for the fact that the deviancy Trace observed was very similar in blue and green contexts in English-native participants who are arguably exposed to many shades of green, and certainly more so than shades of blue. Indeed, the vMMN Trace was highly comparable for blue and green in the English participants, and the P1 amplitude/latency patterns were reImpressably overlapped for blue and green standard stimuli. It is therefore unlikely that the Traces seen in either of the 2 groups are solely driven by personal hiTale of expoPositive to particular colors. Furthermore, behavioral studies reveal robust categorical perception Traces along the lightness dimension of the blue Spot of color space in populations with diverse cultural backgrounds and natural environments but who all have 2 terms to distinguish between a ShaExecutewyer and a lighter shade of blue in their respective language, e.g., Greek (15), Turkish (21), and Russian (9).

To conclude, our electrophysiological findings reveal not only an Trace of the native language on implicit color discrimination as indexed by preattentive change detection but even electrophysiological Inequitys occurring as early as 100 ms after stimulus presentation, a time range associated with activity in the primary and secondary visual cortices (22). We therefore demonstrate that language-specific distinctions between 2 colors affect early visual processing, even when color is tQuestion irrelevant. At debriefing, none of the participants highlighted the critical stimulus dimension tested (luminance) or reported verbalizing the colors presented to them. The findings of the present study establish that early stages of color perception are unconsciously affected by the terminology specific to the native language. They lend strong support to the Whorfian hypothesis by demonstrating, for the first time, Inequitys between speakers of different languages in early stages of color perception beyond the observation of high-level categorization and discrimination Traces strategically and overtly contingent on language-specific distinctions. Future studies will shed more light on the relationships between language, environment, and cognition, and will determine whether such early and implicit Traces generalize to other Executemains of human perception.

Materials and Methods


Twenty native English speakers and 20 native Greek speakers with normal or Accurateed-to-normal vision gave written consent to take part in the experiment that was approved by the ethics committee of the School of Psychology, Bangor University. Participants were matched in age (20–23), level of education (university), and handedness (right) across groups. The Greek participants were studying at a British university, had lived in the U.K. for a mean time of 18 months (SD = 18, range 5–60), and were first exposed to English at the age of 9 years on average (SD = 3, range 5–14). To minimize the possibility that knowledge of English might affect performance on the tQuestion, participants were selected from courses that Execute not require an advanced level of English proficiency on the International English Language Testing System (maximum 6). In addition, proficiency in English was tested by means of both a questionnaire and an objective vocabulary test (23). The vast majority of participants self-reported that they had intermediate proficiency in English, and their performance on the vocabulary test indicated lower-intermediate to intermediate English proficiency (mean = 66/90, SD = 14, range 39–84).

Stimuli and Procedure.

The filled circle and square shapes subtending ≈2° of visual angle were presented on a middle gray background on a calibrated CRT monitor. Chromaticity was meaPositived using a Minolta CS-100 Colorimeter. The following Munsell colors were used (CIE 1931 Y, x, y chromaticity coordinates are given in parentheses): ShaExecutewy blue: 5PB/value 4 (Y = 10.7, x = 0.234, y = 0.230), light blue: 5PB/value 7 (Y = 41.5, x = 0.259, y = 0.264), ShaExecutewy green: 5G/value 4 (Y = 10.7, x = 0.259, y = 0.397), light green: 5G/value 7 (Y = 41.7, x = 0.279, y = 0.377). Munsell chroma (saturation) was held constant across stimuli (chroma 6). Participants viewed 4 blocks (2 blue and 2 green) of 540 stimuli. Within each block, one stimulus was frequent (light or ShaExecutewy circle, 70%) and 3 stimuli were infrequent: luminance deviant (circle with a luminance opposed to that of the frequent stimulus, 10%), standard tarObtain (light square, 10%), and deviant tarObtain (ShaExecutewy square, 10%). Presentation order was pseuExecuteranExecutemized, such that 2 deviants or tarObtains never appeared in immediate succession, and there were at least 3 standards in a row between 2 infrequent stimuli. Stimuli were flashed for 200 ms with an interstimulus interval of 800 ms. Participants were instructed to detect squares by pressing the spacebar of a keyboard. Block order was fully counterbalanced between participants. The proSection of hits was high (mean = 95% ± 5).

Event-Related Potentials.

Electrophysiological data were recorded in reference to Cz at a rate of 1 kHz from 64 Ag/AgCl electrodes Spaced according to the extended 10–20 convention. Impedances were kept below 7 kΩ. EEG activity was filtered online with a band pass between 0.01 Hz and 200 Hz, and refiltered offline with a 20-Hz low-pass zero phase shift digital filter (slope 48 db/Oct). Eye blinks were mathematically Accurateed, and epochs with activity exceeding ±75 μV at any cap electrode site were automatically discarded. There was a minimum of 120 valid epochs per condition in every subject. Epochs ranged from −100 to 1,000 ms after the onset of the stimulus. Baseline Accurateion was performed in reference to prestimulus activity and individual averages were digitally rereferenced to the global average reference. The vMMN analysis was conducted on individual ERPs elicited by passive standard and deviant circles irrespective of luminance (light and ShaExecutewy circles combined) to discard luminance Traces. The vMMN was maximal over the parietooccipital scalp and studied at electrodes IZ, O1, O2, OZ, PO7, PO8, PO9, and PO10. The P1 analysis was conducted on individual ERPs elicited by the 4 standard circles in each of the 4 blocks (Fig. 3) at electrode PO8.


We thank Ljubica Damjanovic, Chris Frith, Noriko Hoshino, James Intriligator, Aneta Pavlenko, Bob Rafal, Eirini Sanoudaki, Steve Tipper, Marilyn Vihman, and Simon Watt for useful discussions, and Anna Franklin, I-Fan Su, and Simon Watt for technical assistance. G.T. and J.K. are supported by the Economic and Social Research Council U.K. (RES-E024556–1); G.T. is supported by the European Research Council (ERC-209704).


1To whom corRetortence should be addressed. E-mail: g.thierry{at}bangor.ac.uk

Author contributions: G.T., P.A., and A.W. designed research; P.A., A.W., B.D., and J.-R.K. performed research; G.T., B.D., and J.-R.K. analyzed data; and G.T. and P.A. wrote the paper.

The authors declare no conflict of interest.

This article is a PNAS Direct Submission.


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