A Cross Cultural Study of Categorical Perception of Color Pre- and Post-Acquisition of Color Terms among Korean and English Toddlers

A Cross Cultural Study of Categorical Perception of Color Pre- and Post-Acquisition of
Color Terms among Korean and English Toddlers
Why is the Investigation of Color Categories Important for Language and Thought?
Understanding color categorizations has broad implications for the debate in cognitive
sciences on the relationship between categories in language and thought. Two important
questions come to the foreground: i) Are terms for color categories arbitrarily derived from
linguistic convention of a culture, or are they “universally constrained” by the perceptual
system? Do color terms affect color perception and cognition to the extent that cross-cultural
differences in those areas are produced?
These questions are important because they have implications for the relativist position
that asserts that language carves up how we think about the world, and that individuals who
speak different languages think about the world differently. Color is an ideal domain for testing
this proposal for the following reasons: i) lexical terms for colors appear to be easily identified,
ii) there is cross-cultural variation in color terms, iii) colors can be quantified using various
scientific techniques and can be manipulated and controlled in experimental settings. Essentially,
the study of color naming and perception is a way of operationalizing the theoretical question of
the influence of language on thought.
Are Color Terms Culturally Arbitrary or Universally Constrained?
The relativist proposal may seem very plausible at first glance given the variation in color
lexicons of different cultures. For instance, languages have different boundaries for color
categories and have different number of color terms. Some languages have non-basic color terms
that are highly contextual and specific (eg. color of cattle skin). However, a systematic analysis

of the World Color Survey (WCS), which collected color terms from speakers of 110 languages
from non-industrialized cultures across an array of colors, suggests that basic color terms are
partially constrained (Kay & Regier, 2007). The analysis shows that even though that the color
lexicons come from languages of different geographical regions, they demonstrate similarities.
Using the Berinmo language as a baseline for comparison, Kay and Regier (2007) found that the
percentage match between the boundaries in the modal naming plot ranges between 69% and
78%. Kay and Regier (2003) also found that the “exemplars”, the centers of color categories,
tend to cluster around similar points in the color space across for speakers of different languages.
Research so far has demonstrated that color lexicons appear to have cultural variation and
“universal constraint”. The notion of “universal constraint” is important because it denotes the
existence of a non-arbitrary property that does not belong to the color lexicons. This leads us to
a new research question: From where and how does the constraint arise? However, this question
is not the focus of the present study, although it will indirectly address the issue as we will
discuss in later sections.
Does Acquisition of Color Terms Affect Perception and Cognition of Color?
There has been extensive debate over the a classic study by Rosch Heider on
cross-cultural variation of color naming and cognition of British and Berinmo participants
(1972). Rosch asserted that the variations in the color lexicons do not influence color cognition;
however, further studies on the same groups have shown that the British and Berinmo adults
demonstrated advantages in distinguishing color differences on a memory task for colors that
cross a boundary that exists in their respective languages (Roberson et al. 2000).

Since then, there are a number of studies that employ visual and memory tasks to probe
the question of the extent to which color terms affect color perception and cognition; many of
which demonstrate contrasting evidence (Roberson, Davidoff, Davies & Shapiro, 2004; Wright,
Davies, & Franklin, 2015). For instance, a longitudinal study of British and Himba children by
Roberson et al. (2004) showed that there was an increasing effect of color terms on memory
errors as the children acquired color terms; those who had not learnt color terms made similar
mistakes. Wright et al. (2015) challenged the aforementioned findings as they failed to detect a
statistically significance based on a null result and Bayesian analysis of the effect of color term
knowledge on a similar memory task among Himba and British children One potential issue with
memory tasks is the results might be affected by memory-related mechanisms; it is difficult to
identify the underlying mechanisms responsible for CP if individuals are required to employ
memory resources (Wright et al., 2015).
Why approach the study of color categorization through developmental linguistics?
In prior sections, we briefly discussed that evidence for “universal constraint” of color
perception pose a challenge to the pure relativist proposal that perception of color is entirely
shaped by linguistic convention arising from culture. Cross-cultural studies that present evidence
of emerging CP effects in accordance to the color lexicons of different cultures among children
should strengthen the relativist hypothesis; however, there still might be prelinguistic universal
CP before acquisition of color terms, and that acquisition of color terms “modify” or
“reorganize” the color categories. The study of infants and toddlers during the linguistic
acquisition stage can help test these hypotheses.

Previous research has shown that color CP effects are found irrespective of color term
knowledge among toddlers at the stage of color term acquisition (Franklin et al., 2008). In an
earlier study, Franklin, Clifford, Williamson & Davies (2005) investigated the extent to which
color term knowledge affects categorical response to perceptual tasks among toddlers at various
stages of color term acquisition. The study found no effect of color term knowledge on the
accuracy of identifying the target color for between-category and within-category differences for
the three color categories (blue-green, blue-purple, red-pink) they tested. Goldstein, Davidoff
and Roberson (2009) replicated Franklin et al.’s study and largely found the same results;
however, one important difference is they conducted an additional naming and comprehension
task to test if English toddlers at post-acquisition stage could use the 11 basic color terms in
English reliably. After conducting the task and additional relevant analyses, they found that only
toddlers who knew the basic color terms demonstrated categorical responses (Goldstein et al.
2009). Interestingly, both Goldstein et al. (2009) and Franklin et al. (2005) found CP at
blue-purple boundaries among Himba toddlers; however, Franklin et al. (2005) found CP at the
blue-green boundary while Goldstein et al. (2009) did not. This led to the conclusion by
Goldstein et al. (2009) that the blue-purple color categorical effect might be attributed to toddlers
having some knowledge of terms commonly used in Himba. It is important to note that they did
not actually test Himba toddlers’ knowledge of these color terms. This speaks to the highly
variable conditions and inconclusive nature of this area of research. Nonetheless, categorical
effects among prelinguistic infants and toddlers who do not use color terms reliably may serve as
important evidence to test the hypothesis that there are universal constraints of perceptual color
categorization. If the blue-purple boundary found in Himba toddlers are not found in

prelinguistic infants and toddlers elsewhere, then the framework under which developmental
linguists are operating will be complicated by the additional factor of relativism in perceptual
color categorization -- that is there is no universal constraints, and if there are, they appear to be
rather loose. The present study also addresses this issue indirectly since we also test a category
boundary -- yeondu (yellow–green) and chorok (green) -- that is unlikely to be universal
perceptually, without language.
Many studies on prelinguistic infants test the same blue-green category have
demonstrated color CP effects. As mentioned before, this serves as strong support to the
hypothesis that color categories are not entirely linguistically constructed, especially since many
languages in the world do not have words that distinguish the colors green and blue. (Clifford,
Franklin, Davies & Holmes, 2009). However, the blue-green boundary perceptual boundary
appears frequently in many cultures, as demonstrated by the World Color Survey (Kay & Regier,
2007), so testing a boundary that does not appear frequently will be important for testing whether
there is universal constraint to color categorical perception.
Is Whorf half right?
One interesting finding from developmental behavioral studies is that pre-linguistic CP is
lateralized to the RH, and that lateralization switches to the LH post-acquisition of color terms
(Franklin et al., 2008). Given the assumption that the LH is dominant for language and that the
visual fields project contralaterally to the brain, half of our perception (RVF) is shaped by
language, and the other half is viewed without the filter of language. In the context of these
findings, we speculate that color terms influence color perception primarily in the RVF. In short,

color lexicons may be shaped by universal non-linguistic properties as discussed earlier, but also
demonstrate variations due to culturally-shaped linguistic convention.
An interesting question for further study is if there are CP effects found in the RH among
toddlers across a boundary that is unlikely to be universal, and if lateralization to the LH occurs
after acquisition of color terms that distinguish the boundary. Research by Roberson, Pak and
Hanley (2008) demonstrated color CP in the LH among Korean adults and none of such effects
among English-speaking adults for the same boundary tested in the present study.
The Present Study: Cross-cultural variation and LH Lateralization
To the researcher’s knowledge, no cross-cultural study on color CP lateralization among
toddlers, regardless of whether they have acquired color terms, has been conducted. Research by
Yang, Kanazawa, Yamaguchi and Kuriki (2016) noted that there are very few recent studies on
lateralization of CP among infants. Clifford et al. (2009) used ERP technique to measure color
CP in infants but did not investigate CP lateralization, given that they used low-density ERP and
non-lateralized stimulus presentations. However, Clifford et al. (2009) established that the
neurophysiological basis for changes in lateralization can be localized using high-density ERP.
Yang et al. (2016) is also the first study to present evidence that colors of different categories are
represented in different occipitotemporal (OT) regions of prelinguistic infants, which also
supports the aforementioned hypothesis that color categories may develop independently before
language acquisition. However, their study did not find significant lateralization among infants.
Our study aims to test the hypothesis that toddlers who have acquired color term
knowledge (henceforth known as “namers”) exhibit color CP that reflect category boundaries of
their native language. This study may also contribute to the discussion of the controversial

hypothesis that there is no universal prelinguistic color CP. If the hypothesis is true, we expect to
see color CP in the RH of toddlers who have yet to use color terms appropriately (henceforth
known as “learners”), since in this study, we replicate the stimuli setup in Clifford et al. by using
a boundary between Korean color categories that does not exist in most languages. The last
potential contribution of this proposed study is to explore whether ERP technique affirms CP
lateralization or not. In sum, this proposed study hopes to contribute to the literature on CP
lateralization and color CP by using high density ERP, a methodology that has not been utilized
in this area of research.
Design and Method
The design and methodology of the present study is derived from Clifford et al. (2009)
and Roberson et al. (2008). This study tests the hypothesis that CP in the LH reflects the
influence of language on the functional reorganization of the brain. It employs a visual search
task with English and Korean toddlers to compare discriminations around the boundary between
the Korean categories yeondu (yellow–green) and chorok (green). Korean speakers are obliged to
make the distinction using those color terms, since there is no single term in Korean that covers
both yeondu and chorok, whereas both colors fall within the “green” color category for English
speakers. If language mediates color discrimination, we predict detection of ERP component in
LH due to CP at the yeondu/chorok boundary in in Korean namers but not in Korean learners,
English learners and English namers. By conducting a cross-cultural study, we also address
concerns regarding the variability of age of color term acquisition. By choosing the
yeondu/chorok boundary, we also attempt to determine if lateralization of color CP around the
time of color term acquisition extend to other color category boundaries beyond the green/blue

boundary that is used in many experiments. We also use high-density ERP as source localization
to detect lateralization. In this study we minimize the variability of the ages of recruited
participants by holding the age constant across the four conditions: Korean-namers,
Korean-learners, English-namers, English-learners. By holding age constant while comparing
two groups of toddlers with different levels of color term knowledge, we are able to eliminate the
possibility that CP lateralization is due to development difference in brain structure. In terms of
order of tasks, we assess toddlers with comprehension tasks followed by naming tasks.
Subsequently, we assess the target detection stimuli before other focal non-target stimuli.
Scalp-derived ERP is a cost-effective and easily available tool. In contrast to fMRI and
PET methods, ERP methods offer a high temporal resolution, which allows researchers to obtain
real-time analyses of the neural processes elicited during cognitive task. We use high-density
scalp-derived ERPs in order to detect the CP lateralization and record the distinct components of
the ERP signal. We will perform the test in an acoustically shielded and dimly lit room. Each
toddler will be seated at a chosen distance away from a computer monitor. A video camera will
be mounted above the monitor and centered on the toddler’s face allowed for recording of gaze.
On the monitor, we show each colored target in either the left- or right-visual field on either the
same- or different-category background, with equal hue separation for both conditions, and we
present it for specified duration (in milliseconds). The researcher will observe each toddler
during the testing session via video camera, and employ on-line judgments to present pictures
only when the toddler was attending to the monitor. Specifically, if the toddler looked away in a
trial, an “attention getter” stimuli was presented and that trial and the subsequent trial were

excluded from analysis. Any trials in which the toddler blinked after stimulus presentation will
also be deleted.
Naming and Comprehension Task
Before we can begin the target-detection task, we need to find out if a toddler has reliable
knowledge of a color term. In order to do so, we assess the toddlers on color term knowledge of
focal stimuli (yeondu and chorok for Koreans , green for English namers), non-focal stimuli
(variations of the focal stimuli) and a select group of focal non-target colors that are found in
both Korean and English (yellow, red, purple, blue). We assess knowledge of focal non-target
color terns because children may over extensively apply color terms outside of the color
category. We expect “namers” to apply color terms to exemplars of the focal stimuli color
accurately.
We design the comprehension task in form of a game, by asking toddlers to point to a
cartoon cat holding a kite of a certain color. The stimuli within a set, which contains the target
and focal colors, are kite-shaped paper cuts pasted next to the cartoon cat. Both figures are
placed on a gray background. Toddlers were asked “which cat is holding the X color kite?”
where X indicates a given color term. For the target detection stimuli, there were two trials (X =
yeondu or chorok), and on each trial children were also asked, “Are there any other cats holding
the X kite?” We also run trials for each focal non-target color (eg. X = red). Similarly, we design
the naming tasks in form of a game by asking the toddlers to name the color of the cartoon cat’s
kite verbally. The setup is similar to the comprehension task, except toddlers will be asked
instead “what color is the cat’s kite?”
Grouping the “Namers” and “Learners”

We tabulate the number of accurate responses in the naming and comprehension tasks for
the color terms yeondu and chorok for Korean toddlers and the color term green for English
toddlers. These measures of accuracy will be used as variables for a principal components
analysis that explained the variance of the individual accuracy measures. Using this component
we are able to calculate weights which provide a reliable measure to divide the toddlers into
“namers” and “learners”. We also cross-check with the accuracy scores of toddlers for focal
non-target colors. We expected toddlers with positive weights to be generally accurate at naming
and identifying yeondu and chorok target detection stimuli and identifying yeondu and chorok
focal stimuli. We also expect that these toddlers are largely accurate in naming and
comprehension tasks of focals for other color categories. These toddlers are classified as
“namers”. The others who made mistakes in the tasks described above who had negative or
minimal weights were labeled as “learners”.
Figure 1. Characteristics of the stimulus display and stimuli.
(a) Stimuli crossing the boundary between the Korean YG (Yeondu) and G (Chorok) categories (A-B =
within-category pair, B-C= cross-category pair).
(b) Illustration of the display. The stimuli varied in hue at constant value and chroma.
Control Task and Behavioral Post-Test
We added a control task in which we displayed the target-detection stimuli in the visual tasks
alternately. The purpose of the control task is to ensure any differences in the ERP components

for the within- and between-category deviants could be attributed to categorical status of the
target-detection stimuli in relation to the standard, rather than on other features of a particular
stimulus. In the control task, we remove the categorical context of the target-detection stimuli by
not displaying the non-focal stimuli (variations of yeondu or chorok).
We predict that on the control task there will be no differences in the ERP components
elicited by the target stimuli. This indicates that there is a similar amount of attentional allocation
(N400) and stimulus updating and encoding in working memory (PSW) for the target stimuli
when the categorical context, that is the background stimuli, is removed. This validates the
experimental design in so far that the preference demonstrated was dependent on the categorical
context of the stimulus in the target detection task.
Immediately after the Target-Detection Task and the Control Task, we present 5-second
trials of paired presentations of the target-stimuli that appeared both tasks. Two researchers will
code the infant looking times based on the videotape data. We also expect that there will be
longer looking times for the target stimulus after the target-detection task but not after the control
task. This post-test should also support that preference for stimulus depends on categorical
context, not arbitrary features
Target Detection Design and Procedure.
Adjacent stimuli in Fig. 1 form within- and between-category pairs. One of the stimulus
in a pair will appear as the target, with the other stimulus as the background. This arrangement is
reversed in half of the trials. The target can be radially located in 10 possible locations. We
randomly allocate the location of the target, with the only constraint that each of the target
appears with an equal number of times on the left and right for within-category and

between-category conditions. To ensure the same ratio of signal to noise across stimuli, an equal
number of trials were included for each stimulus for a given toddler.
Predicted Results and Source Localization Analysis:
This study’s predicted results are derived from Clifford et al. (2009) and Yang et al.
(2009). We expect the following ERP components to be elicited when the target stimuli is
detected: a) negative slow wave, b) positive slow wave and c) central negativity that peaks
around 400ms (N400). The N400 is commonly interpreted as a marker of attentional allocation.
PSW and PSW are interpreted as reflections of diffuse activation of neural areas. Specifically,
the NSW reflects the detection of novel events against a background of familiar events, and the
PSW reflects the extent of stimulus encoding and updating in working memory.
In order to identify the current generators underlying ERP components, we create current
source density (CSD) maps using a map tool integrated in a computer software called
Brainvision Analyzer. We use CSD maps to substantiate the topographic ERP results, since they
provide a reference-free, spatially enhanced representation of the location, intensity, and
direction of underlying current generators (Trimmer et al., 2017). We also calculate the language
laterality index (LI) of mean ERP amplitudes of the left (L) and right hemisphere (R) using the
formula LI = (L−R)/(|L|+|R|) based on a recent ERP study investigating lateralization of
language function in epilepsy patients (Trimmel et al., 2017). Since we hypothesize that ERP
amplitudes are more negative over the language dominant hemisphere, we classify the LI in the
following manner: LH dominant (LI < −0.2), bilateral (−0.2 < LI < 0.2), or RH dominant (LI >
0.2). In estimating the source of the N400 waves, we also follow the precedence of Trimmel et
al. (2017) by paying attention to the middle and anterior temporal and inferior frontal regions

when observing the lateralized CP effects. It is worth noting that the ERPs in the aforementioned
regions are found among adults; it might be the case that it is different for toddlers.
Based on our hypothesis that language affects the categorical perception of color, we
expect lateralized effects to the LH among the Korean “namers” in those areas. In the context of
the our study, we expect to see no CP effects among all groups except for the Korean “namers”.
For the Korean “namers”, we estimate that the regions contributing to the N400 peak will be
from the left regions.
We expect that at all electrodes, the between category target-stimulus will demonstrate a
larger negative amplitude on the N400 than the within-category stimulus at the LH. We expect a
strong amplitude of N400 between the voltages of -10 to -20 as demonstrated by Clifford et al.
(2009). We also expect a lack of categorical effects in the first 100ms after stimulus onset among
infants in contrast to ERP studies among adults in which categorical effects have been found in
visual ERP components as early as 90ms (Holmes, Franklin, Clifford & Davies, 2009). This
phenomenon suggests that infant CP depends more on attentional mechanisms rather than early
perceptual mechanisms. We also expect that stimuli that are from the same category with the
background color will elicit a PSW. The PSW for the within-category target stimuli may indicate
that the stimulus is being incorporated into the representation of the background stimuli category,
and that category is being updated.
There should be a greater amplitude of NSW for the between-category target stimuli and
little to no difference for within-category stimuli. The expected results should be consistent with
novelty preferences studies of CP, in which the within-category color is equally novel (as
demonstrated by the lack of difference of NSW) as the repeated or background stimuli. It has

been argued that the NSW is a reliable marker of within-category similarities in other CP
domains (Quinn, Westerlund & Nelson, 2006). In our study, we did not create a test condition in
which we displayed the same color as background and target, so we are unable to demonstrate if
there are indeed equivalent slow waves for the background and the within-category deviant as
Clifford et al. (2009) has shown. In any case, Clifford et al. (2009) found equivalent amplitude
for within-category deviant and background stimuli, and greater amplitude for between-category
stimuli than the within-category stimuli in both NSW and N400. One interpretation is that at
least in the color domain, the underlying mechanisms are the same for identifying whether a
color belongs to the same or different category as the background display.
This present study also clarifies issues regarding the CP effects in the RH in visual search
tasks. If strong categorical effects are found in RH among Korean “namers” for our study, it
lends support to previous claims that CP effects in RH found in previous studies among English
adult speakers for a common color boundary (blue-green) cannot serve as evidence for the
existence of prelinguistic universal categorization of colors (Roberson et al., 2008), since the
Korean-specific boundary is unlikely to belong to a universal set of categories, based on findings
of the WCS. However, if strong categorical effects are found in RH among Korean “learners”,
then it may serve as strong evidence that there are no universal pre-linguistic color
categorization (Clifford et al., 2009). Although pre-linguistic color categorization is not the focus
of the present study, it is important for further research to investigate the perceptual and
cognitive processes that underlie CP effects among toddler “learners” and prelinguistic infants in
order to establish whether and how color CP provides constraints on linguistic color
categorization later in development.

References
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