the emergence of color cognition from color perception

N. Louanna Furbee and Kelly MaynardDEPARTMENT OF ANTHROPOLOGY, UNIVERSITY OF MISSOURI, COLUMBIA/. Jerome SmithDEPARTMENT OF ANTHROPOLOGY, UNIVERSITY OF SOUTH FLORIDARobert A. Benferjr., Sarah Quick, and Larry RossDEPARTMENT OF ANTHROPOLOGY, UNIVERSITY OF MISSOURI, COLUMBIA

The Emergence of Color Cognitionfrom Color Perception

Reporting isomorphism between the perception and cognition of color, thisarticle speculates upon how the two might interrelate and how that relationmight be constrained. A pilot study of color perception revealed differences inthe perception of color by sex and by eye color of subject. In the present study,we examine results of a triadic sorting task of color terms, finding that for thenine most salient terms in the subjects' color cognitions, the sortings of menand women varied significantly along two of the meaning dimensions revealedin the perceptual experiment. Differences were also found in the cognitions ofblue-eyed and brown-eyed persons for the same nine terms. We argue that thecognition of color may be governed by two kinds of constraint: one that limitsthe level of abstractness the perceptual forms can evince, and one (based onconnectedness) that governs the mapping of perceptual structures into theircognitive expressions in any language and culture.

Chad McDaniel's study of the biology of perception and the variabilityin kind and number of color terms among human societies led himto the revolutionary proposition (Kay and McDaniel 1978; McDaniel

1972) that color terms were "basic" in the sense defined by Rosch and herassociates (Rosch and Mervis 1975; Rosch et al. 1976). Basic terms are notarbitrary and, for objects, are linked to function. In the realm of colorperception, these terms were given an evolutionary sequence.

Journal of linguistic Anthropology 6(2):223-240. Copyright © 1997, American AnthropologicalAssociation.

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224 Journal of Linguistic Anthropology

We report here the results of several experiments that, while in generalsupporting the findings of the pioneering work of Berlin and Kay (1969),add a new property of color classification, differences in perception andcognition that are influenced by sex and eye color.1 We now know that thesedifferences may have a genetic component for perception (Neitz et al. 1991),although we did not expect to find differences by sex or eye color when webegan the research. We attempt to explain the results as consonant with aconnectionist perspective of constraint satisfaction on neuropsychologicalprocesses. We also speculate that natural selection during the Pleistocenecould have given rise to sexual differences in color perception, differencesof adaptive significance. Eye-color differences are perhaps best explainedby their weak linkage with skin color, associated with reproductive isola-tion. We suggest that future research should examine cultural cognition ofcolor as related to perceptual constraints via intermediate, stepwise stages,possibly at the level of individual features. We consider the possibility ofjudging the naturalness of a feature from the perspective of the idea ofmarkedness. The degree of organization attributable to eye-color and sexdifferences points to biological constraints that may be extended or re-stricted by cultural processes.

The data for this study are from a series of experiments of color classifi-cation as practiced by samples of American college students. We examineconclusions from research on both color perception and color-term cogni-tion and discuss how the two interrelate. We report findings from twostudies of color classification, the first requiring subjects to complete aperceptual task and the second involving a cognitive task. The factorsconsidered are eye color and sex.

Reporting on pilot studies of color perception, Furbee (1992) offeredevidence that both eye color and sex affect how individuals perceive color.She found that persons could be distinguished for eye color and by sex,based on their responses to a perceptual triadic sorting task of 13 Munsellcolor standards.2 It is these results from her perceptual studies that wereused in the present study for comparison with results of a cognitive triadicsorting task of color terms.

Possible Genetic Foundation for Color Perception

Recent psychophysiological research argues that there is a genetic basisfor difference in color perception between men and women (Merbs andNathans 1992; Mollon 1992; Nathans 1991; Nathans et al. 1986a, 1986b;Neitz et al. 1991; Winderickx et al. 1992), a conclusion that would helpexplain the findings from Furbee's pilot studies. Color vision is at least inpart a sex-linked trait. The amino acid position #180 at exon #3 on theX-chromosome is polymorphic for either alanine or serine (Neitz et al.1991). Merbs and Nathans (1992) and Winderickx et al. (1992) investigatedthe psychophysical correlates of the genetic polymorphism. Of 50 whitemales with normal color vision, 62 percent had the hydroxyl-bearing aminoacid serine at position #180; the remaining 38 percent had alanine. Thispolymorphism was used to explain the differences in color matching results

Emergence of Color Cognition 225

among the subjects. Since women have two X-chromosomes and can po-tentially be heterozygous for the genetic material in exon #3 coding forami no-acid position #180, it is possible that women heterozygous at thislocus could be tetrachromic and thereby capable of seeing an extra dimen-sion of hue never experienced by homozygous males (Mollon 1992).

Nevertheless, it was not certain that the differences between the perform-ance of men and women found in Furbee's perceptual study could havebeen solely due to genetic difference in the color vision of men and women,or at least that such difference would result only from the fact that womencan be tetrachromatic for these traits and men cannot. In fact, Neitz andNeitz (1995) have recently reported that some men also may be tetrachro-matic. Further, the color cognitions of men and women are widely assumedto be different; perhaps the differing color cognitions of women and menmight also have affected their performances on the perceptual task. Conse-quently, to examine the structures of response to these perceptual andcognitive color tasks, we designed a study of color-term cognition that wasclosely comparable with Furbee's previous perceptual one and analyzedthe results for the variables of eye color and sex. This article reports thefindings of the studies and the results of their comparison.

The Experiments

Perception

The perceptual experiment used 13 color standards from the Munsellarray.3 These represented colors that can be glossed as: Red, Yellow, Or-ange, Green, Blue, Pink, Purple, Chartreuse, Beige, Turquoise, White, Black,and Gray. All possible combinations of these 13 triples yielded 286 triads.These were randomized both within the triples and in the order of presen-tation of each triad. The subjects were 10 male (5 brown-eyed and 5blue-eyed) and 14 female (7 brown-eyed and 7 blue-eyed) young adults inColumbia, Missouri. Eye color was determined by the interviewer. Eachconsultant was screened for color blindness using the Ishihara color plateprior to participation in the perceptual experiment and removed from thestudy if tested positive.

Triads were presented to each consultant as triples of Munsell chipsagainst a Kodak grey background, and the subject was asked to identify thetwo of the three in each triple that most resembled one another. The pairsof color chips judged similar were recorded. The test never asked for a colorterm or for identification of a color chip by name and, so, was thought freefrom direct influence from cognition.

Similarity judgments were analyzed using a nonmetric variant of anindividual-differences multidimensional-scaling model (the INDSCALmodel in program ALSCAL [Tukane et al. 1977] in the SAS statisticalpackage [1992]). Three relevant dimensions were found with acceptablestress and in correspondence with examination of the scree of stress values;these could be labeled as nonhue/hue, as warm/cool (or light/dark), andas yellow-green/yellow-red.

226 Journal of linguistic Anthropology

Figure 1 shows the male/female results combined. The first (horizontal)dimension (nonhue/hue) isolates White, Black, Gray, and Beige from allother color standards in the task. It should be mentioned by way ofexplanation that consultants sometimes volunteered that some or all ofthese four were not colors, or that they were the absence of color or thecombination of all colors. Such statements indicate learned explanationsrather than reports of perception. Dimension 2, the vertical dimension, splitthe warm light categories from the cool darker ones.

The third dimension, the vertical one as seen in Figure 2, opposedyellow-green against yellow-red. Interestingly, this dimension is morepronounced in the results from the women.

Figure 3 shows how it is possible to distinguish men from women bytheir perceptual responses to color on the first two dimensions. Females liealong a line of correlation between dimension 1 (nonhue/hue) and dimen-sion 3 (yellow/green versus yellow/red), whereas men lie along a line ofnegative correlation between the two dimensions. Exceptions include threewomen and one man. Thus 9 of the 10 males and 3 of the 14 females are thesource for the nonhue-versus-hue contrast.

Figure 4 shows that blue-eyed and brown-eyed subjects could be distin-guished by their responses on the perceptual test (B = brown-eyed, L =blue-eyed). The effect of eye color on perception was strong in the resultsfrom a multiple linear discriminant function (Baysian classification) wherecorrect eye color was predicted for 8 out of the 10 men. On the other hand,the same test predicted the correct eye color for only 8 out of 14 women.

Cognition

For the cognitive experiment, 278 students in three introductory anthro-pology classes at the University of Missouri, Columbia, were asked tocomplete a questionnaire that asked their eye color and sex. At the sametime, the students listed all the color words they could think of in atwo-minute period. This free-listing task was based on one developed bySmith (1992). We also employed Smith's extension of the idea of saliencereported in the same publication. We combined frequency and rank scoresfrom the free listing to determine the 27 most salient color terms for thispopulation (Smith et al. 1995).

Using Anthropac version 4.6 (update of 4.0; Borgatti 1994), three sets oftriads were developed (see Table 1). The first set of triads was constructedfrom the nine most salient terms from the free-listing task: Blue, Red, Green,Yellow, Black, Orange, Purple, White, and Brown. Note that this list over-laps that used in the first experiment in that eight of the nine terms in thislist label the same color categories represented among the 13 color stand-ards used in the perception study. The second set of triads was derived fromthe terms ranked 10 through 18, and it included Pink, Gray, Violet, Gold,Magenta, Silver, Tan, Maroon, and Turquoise. The third set came from thenext nine most salient terms: Mauve, Indigo, Teal, Fuschia, Navy, Aqua,Lavender, Beige, and Burgundy. One month after the free-listing task wasperformed, the same classes who had participated in the original effort


§

•~ It I I IIV r l l . w

Figure 1Results of nonmetric individual-differences multidimensional-scaling analysis(from both male and female subjects) of the perceptual task, showing thatdimension 1 (horizontal) represents nonhue versus hue, and dimension 2 (verti-cal), warm versus cool.

1

Vrllt-*

i

• i • ,

II i

Ch.ii h ii .• 1 - 1 •

Figure 2Results of nonmetric individual-differences multidimensional-scaling analysis(from the female subjects) of the perceptual task, showing again dimension 1(horizontal), the nonhue-versus-hue dimension, and dimension 3 (vertical), ayellow/green-versus-yellow/red dimension, which was seen most stronglyamong women.


NON-HUE HUE

Figure 3Results of nonmetric individual-differences multidimensional-scaling analysisof the perceptual task, showing that men and women could be distinguished bytheir responses on dimension 1 (nonhue versus hue) and dimension 3 (yel-low/green versus yellow/red), o = female; y = male.

88

B L l I I VED

I

I L

>•

BROWN-EYED

IILUE-E1ED

I :

Figure 4Results of nonmetric individual-differences multidimensional-scaling analysis(from both male and female subjects) of the perceptual task, showing thatbrown-eyed subjects could be distinguished from blue-eyed subjects by theirresponses on dimension 1 (nonhue versus hue) and dimension 2 (warm versuscool). B • brown-eyed, L - blue-eyed.


Table 1The 27 most salient color words supplied on the free-listing task by the 278subjects

Color wordBlueRedGreenYellowBlackOrangePurpleWhiteBrownPinkGrayVioletGoldMagentaSilverTanMaroonTurquoiseMauveIndigoTealFuschiaNavyAquaLavenderBeigeBurgundy

Frequencyof mention

24825425625424723822621621220318313413586

117105

9086786072616252606552

%909293928986827877746648493142383331282226222218222419

Rank3.534.205.406.017.207.608.539.028.67

10.6312.1810.5814.0410.7914.6813.9612.9713.1712.9111.2013.5712.1013.9511.6513.1213.9113.48

Salience0.7720.7580.7010.6680.5850.5430.4850.4370.4410.3590.2650.2350.1640.1530.1320.1260.1190.1190.1130.1040.0960.0940.0840.0820.0790.0760.065

completed one of the three versions of a written triadic sorting task. Thethree versions were distributed to the classes according to a random butcomplete design: the first (most salient) set was given to 78 subjects, thesecond set to 76 subjects, and the third (least salient) set to 76 subjects. Thedistribution was such that approximately one-third of each of the threeparticipating anthropology classes received each of the three sets. Werequested that participants circle the two color terms of the three in eachtriple that most resembled each other.

After collecting and collating the triadic data from the three classes, wematched them with the personal data regarding sex and eye color obtainedfrom the initial questionnaire via the student identification numbers. Be-cause the data were collected on two different occasions and becauseattendance varied in these large lecture sections, we were unable to match

230 journal of Linguistic Anthropology

all students; so the sample size for analysis was decreased by about one-fourth.

Analysis and Findings

For analysis, we used the SAS program MDS (SAS 1992) configured asindividual nonmetric multidimensional scaling to analyze our data, fur-thermore, options in the program were set to produce results congruentwith INDSCAL, which was used in the previous perceptual study. Figure5 shows the nonmetric individual multidimensional plot of the triadicsortings of the nine most salient color terms.

In the plot in Figure 5, one can see the cognitive distance among the colorsbased on the mean distances determined by the percent agreement. Onlytwo dimensions are presented as there are only nine terms, a numbersufficient for a two-dimensional solution in the individual-differences formof nonmetric multidimensional scaling. Looking at the vertical dimen-sion—dimension 1—we see that the students conceived of the similaritiesof the color terms from light or warm to dark or cool. The plot reveals thatalong the horizontal dimension—dimension 2—subjects categorized theterms according to nonhue (or noncolor) on the left to hue (or color) on theright.

• BLUE .PURPLE

•BLACK

• DROWN.GREEN RED

.ORANGE

tHXO

ELLOU

NON HIM Ml I

Figure 5Results of nonmetric individual-differences multidimensional-scaling analysisof the cognitive triadic sorting task based on the nine most salient color termsfrom the free listing, showing that these terms are distinguished according to alight-versus-dark or warm-versus-cool dimension (dimension 1, vertical) and anonhue-versus-hue dimension (dimension 2, horizontal).

Emergence of Color Cognition

The multidimensional scaling of the results from the triadic sortings ofthe second set of nine color terms is given in Figure 6. The dimensions thatdistinguish members in the second set of color terms are predictably moredifficult to gloss. Dimension 1, the vertical one, appears to represent boththe hue versus nonhue and the dark versus light distinctions. Dimension 2appears to distinguish cool from warm, or perhaps blue from red.

Similarly, for the third set of terms, dimension 1 differentiates red orwarm from blue or cool, whereas dimension 2 can be labeled light on theleft and dark on the right (Figure 7).

We analyzed the effects of sex and eye color on individual weighting ofdimensions by using MANOVA (multivariate analysis of variance, asimplemented in SAS 1992). For the first, most-salient set of color terms(Blue, Green, Red, White, Yellow, Orange, Purple, Black, Brown, shown inFigure 5), the categorization showed statistically significant differencesaccording to sex for both dimensions and near statistically significantdifferences by eye color. For sex, the difference was significant at the .05level; for dimension 1 (the one we glossed as light versus dark, or warmversus cool), a value this large or larger would occur by chance alone fewerthan 4 times out of 100, and for dimension 2 (nonhue versus hue) fewer than3 times out of 100.

i|+ SILVERO 'TAN

z -curv

•TURQUOISE

MA CENT A

2 -V.OLET "MAROON

COOl-imil ' II _ WARM RED

Figure 6Results of nonmetric individual-differences multidimensional-scaling analysisof the cognitive triadic sorting task based on the second most salient set of ninecolor terms from the free listing, showing that these terms are distinguishedaccording to a vertical dimension (dimension 1) that can be glossed as hue versusnonhue or dark versus light, and a horizontal dimension (dimension 2), coolversus warm or blue versus red.

Journal of Linguistic Anthropology

oS -TEALS3

-NAVY-AQUA

•INDIGO

•BEIGE -LAVENDER

•FUSCHIA

•MAUVE•BURGUNDY

g LIGHT DARK

Figure 7Results of nonmetric individual-differences multidimensional-scaling analysisof the cognitive triadic sorting task based on the third most salient set of ninecolor terms from the free listing, showing that these terms are distinguishedaccording to a vertical dimension (dimension 1) that can be glossed as red/warmversus blue/cool, and a horizontal dimension (dimension 2), light versus dark.

In the case of eye color, the probability value was 07 on both dimensions.The chances of wrongly concluding that there are genuine cognition differ-ences between the brown-eyed and blue-eyed persons for either dimensionin this sample are 7 out of 100. That is, even if there were no differencesbetween brown-eyed and blue-eyed persons, 7 samples out of 100 wouldproduce a difference this large or larger by chance alone. Although thisfigure does not quite reach the typical .05 level commonly used in the socialsciences, the fact that both dimensions have a .07 level suggests that a realdifference is being measured.

There is no reliable difference between the way either men and womenor people of different eye color categorized the second and third set of lesssalient color terms. The higher degree of salience of the first set of colorterms (mean = .599) may account for the fact that sex and eye-color differ-ences existed for it, while the lower salience for set 2 (mean = .186) and forset 3 (mean = .088) meant some individuals may not have been familiarwith all the colors. For the most salient basic terms, the same two dimen-sions, nonhue versus hue and warm versus cool, are identified in theperceptual task (Figure 1) and validated by their appearance in the cogni-tive task (Hgure 5), even though only some of the colors are common toboth. Sex and eye-color differences, first suggested in the smaller perceptualstudy, are confirmed in this larger cognitive study.


Relating Cognition to Perception

Our major findings were three: (1) The results of a cognitively based task,the triadic sorting of color terms, were isomorphic to those of a perceptualtask, a triadic sorting of color samples. The same underlying dimensions ofcolor were apparent in both. (2) There was a strong male/female differencein the performance of these tasks. (3) There was a perceptible, but lessstrong, difference by the eye color of the subject. The weakness of this effectmay have been due to our using phenotypes for the perceptual study thatwere clearly blue or brown and using phenotypic identification for thecognitive study from self-reporting. Thus in the latter study, dark hazel mayhave been reported as brown, and green may have been reported as blue.The genetics literature clearly distinguishes between brown, green (includ-ing hazel), and blue; therefore, the comparisons we are making with thegenetics literature may be somewhat skewed. Nonetheless, both perceptualand cognitive studies detect some difference.

The latter two findings of male-female difference and eye-color differ-ence direct us to a consideration of a genetic basis for color perceptionvariation, more subtle and more general than the well-known sex linkingin color-blindness disorders. Since the genetics of a species can be regardedas a direct record of its evolution, it points us in this instance to a consid-eration of the likelihood of pervasive constraints on cognitive developmentin these terms.

What can these findings mean for the issue of the relationship betweencognition and perception? In considering this question, we speculated thatperception is more likely to approach a representation of the universalfoundation upon which any cognition can be built and, indeed, is a candi-date for any formulation of universals. With that assumption, we shouldconsider what the nature might be of the constraints on building a culturalcognition, in addition to the limitations that perception places on anycognition. Such limitations might be the equivalent of well-formednessconditions. As a candidate for such a constraint, we explore here thepsychological principle of connectedness. The theory of connectedness(Shepard 1994) is one variant of the general connectionist enterprise, anapproach that in its most common form attempts to model human thought,language, and learning, among other domains, as a series of nodes thatchange states—that are activated—depending on the state of other nodesto which they are connected. Shepard motivates this approach as a logicalconsequence of the fact that human beings have evolved in interaction withthe physical conditions of this planet, an environment that has shaped themso that they rely in fundamental ways upon manipulation of objects—and,we add, their reflectivity—in three dimensions. It can be argued that theidea of a continuous symbol system, in contrast to discrete symbol systems,is a chief identifying marker for connectionism (MacLennan 1994). Theconcept of prototypes with fuzzy boundaries was adopted early to explainmapping of color terms by the pioneers in this area (see Kay and McDaniel1978 on color foci and boundaries).


For some connectionist-driven investigations, logic and semantic repre-sentations are treated as epiphenomena, an approach that has not beenpursued in linguistic anthropological investigations of color. For otherinvestigators, a hybrid of classical and connectionist approaches providesan effective model. Connectionism is commonly associated with neuralnetwork analysis, the modeling of human perception and cognition in acomputer program that, to some extent, is based on the neurologicalorganization of the central nervous system (CNS). But connectionist ap-proaches range from conceptual mapping and semantic networks to geo-metrical representations of similarities among terms or stimuli. Research inthese areas is burgeoning.

We have argued elsewhere (Benfer et al. 1996) that neural networks, thebest known of the connectionist approaches, are unlikely candidates forrepresenting ethnographically developed knowledge structures. In thepresent example, however, where eyes are the only visible portion of theCNS, we sketch an explanation based on linguistic-like constraints onbehavior that, although culturally mediated, lies close to biological sub-strates. Following Shepard, the metaphor that we choose is the natural oneof spatial representation.

This principle has been given in geometric terms as a working hypothe-sis:

[T]hat the region in representational space corresponding to a basic kind is aconnected region. Between the points corresponding to any two objects of thatkind, then, there is always a continuous path in the representational space thatfalls entirely within the consequential region for that kind. [Shepard 1994:23]

From this point of view, any two variants of a basic kind (say of a chair, adog, a "red") would be connected via "a continuous path in repre-sentational space that falls entirely within the consequential region for thatkind" (1994:23). Such a characterization relates variants according to thedichotomous criterion of connectedness rather than along a graded meas-ure (Rosch and Mervis 1975; Rosch et al. 1976). According to Shepard, as adichotomous measure, connectedness would have the advantage of repre-senting sharp boundaries between objects; it would not necessarily pertainto nonbasic categories, such as the less salient color terms treated here.

Connectedness is a constraint on the relation of one entity to another, ahypothesis about how the cognitive world is constructed upon perceptualground. It resembles the linguistic idea of constraints on the character ofunderlying entities, on the abstractness of underlying representations. Thelinguistic idea extended into this perceptual/cognitive discussion wouldpertain to the possible characters or inventories of hypothetical fundamen-tal perceptual forms, relations, or processes. Connectedness, on the otherhand, would pertain to the paths by which these fundamental perceptualentities could be mapped onto the variety of the world's cognitions. Forconvenience, we can think of such a linguistic-derived idea as a constrainton perceptual form (or process).


Let us elaborate first on this suggestion about possible underlying per-ceptual entities by interpreting our results under three versions of thisextended idea about possible characters of underlying perceptual entitiesor processes. We will later return to the idea of connectedness as a meansof constraining the building of cognition (or the mapping of perception ontocognition).

A weak form of a perceptual form constraint might be something like thefollowing:

Every hypothesized (perceptual) entity must also be a variant in the cognition ofthe same language or culture, data from which are the basis of the formulation.

Linguists will recognize this as a rephrasing of an early dictum of NaturalGenerative Phonology that required an underlying segment in the phonol-ogy of a language to be drawn from the inventory of surface variants in thatlanguage. Our results clearly meet this requirement; but without adding atheory of preference for selection (such as markedness, economy, primacyof acquisitional sequences, et cetera), one would gain little insight into howa cultural or individual cognition might be constructed according to theconstraint since any existing variant in the cultural inventory would beequivalently available. It is difficult to impart directionality to any suchmodel since there would presumably be a similar number of perceptualentities to the cognitive ones. But color terms do have acquisitional se-quence (Dougherty 1977; Harkness 1973); they are hypothesized also to beevolutionarily derived, and the basic color terms can be viewed as un-marked, with nonbasic color terms as marked. Further, economy can bedemonstrated in reducing the space of color to two or three dimensions.

Another, stronger version of a perceptual form constraint might allowperceptual entities that were unknown or even impossible in the culturalcognitions of the world. So, analogously, analytic formulations of colorperception could underlie a cultural cognition that claimed the three wavesof the light signals were processed not into the four fundamental hue-basedproducts of the opponent cells but into five, eight, or however many signalsas might be convenient to the analysis (Hering 1964[1920]; Kay andMcDaniel 1978). The problem with such a strong version is that the exuber-ant eclecticism that it exemplifies would seem to fail to capture possibleisomorphisms between neurophysiological reality and perception—andwould therefore be problematic as a theory, since a theory of everything isbut a theory of nothing. Such a strong constraint would be difficult toaccept. Again, linguists will recognize highly abstract analyses as fulfillingthis version of the principle; for example, the famous analysis of Tiibatula-bal (Swadesh and Voegelin 1939) that hypothesized a voiced glottal stop inthe underlying phonological inventory, something physically impossibleto produce.

We would suggest instead that a suitable formulation of this constrainton perceptual form might be something like the following:


That an abstract perceptual entity that is hypothesized as fundamental to aparticular cognition must have a superficial cognitive equivalent in some linguis-tic or cultural cognition, but not necessarily in the one under examination.

This formulation limits candidate perceptual entities to those for whichactual existence is known in cognition and, so, offers a principled restric-tion. It further invites markedness principles. In attempting to account forour somewhat surprising results regarding the topology of judgments ofsimilarities among color terms and color standards, based on individualdifferences in perception (Figure 1) and cognition (Figure 5), we can buildan account that will accept connectedness as a plausible perceptual con-straint on the construction of cognition. This principle would dictate thatvariation in a linguistic and cultural cognition be related to the perceptualfoundations via intermediate, stepwise stages. Each intervening stagewould also be required to meet the perceptual form constraint and, so,would also be a possible superficial cognitive form or process in somelanguage or culture of the world. By Shepard's criterion, these forms wouldhave to be sequenced in such a way that neighbors would differ from oneanother by a minimal measure, perhaps by one feature or attribute alone.Further, some representations—or perhaps features—would be more fun-damental than others, more like root features. These would be candidatesfor perceptual forms, relations, or processes themselves or for componentsof them. In the present study, the nine most salient terms, as basic terms,would be candidates for perceptual forms, as would their components, suchas the meaning dimension of nonhue versus hue. The representation of thestructure of such forms and processes in the Euclidean space of multidi-mensional scaling has been demonstrated to have psychological reality(Furbee and Benfer 1983; Shepard 1980).

If connectedness were married to an extended idea of markedness, wewould also have a conception of a greater likelihood or naturalness of aparticular feature or form such that it would be fundamentally more likelyfor an element to resemble its neighbors than for it to be vastly differentfrom them. We might find, however, considerable cultural variation in theperceptual and cognitive expression of these putatively universal proper-ties. A clear example of such a situation can be seen in the extended Berlinand Kay hierarchy of stages for the development of basic color terminolo-gies in the world's languages, where not only is there an evolutionarysequence mirrored by the developmental one but also some mathematicalpossibilities are ruled out (Kay et al. 1991). Further (and cast a differentway), a "vantage" (MacLaury 1992) could be viewed as a specific culturalpreference (or individual preference, or situational preference) that mightbe common among the world's languages for the treatment of color and,therefore, greatly unmarked. On the other hand, a particular configurationor vantage might be rare (although possible) and, therefore, highly marked.The case of the yellow-pale green linking in Salish languages (MacLaury1987; MacLaury and Galloway 1988) or the concern with lesser saturationin Japanese (Stanlaw 1987) would be examples of this second case. Some


vantages should be ruled out by this constraint, however, since not alllogical possibilities actually appear, even rarely.

As mentioned, Shepard proposed that there is an evolutionary basis forconnectedness. He argued that a science of mind can perhaps be con-structed by virtue of the evolutionary internalization of universal regulari-ties in the world; for example, three-dimensionality could be thus viewedas predominant in human thinking just because the nature of this planethas selected for three-dimensional representation. Looked at in this light,we can say that the dimensions revealed in the present studies are them-selves candidates for being root or fundamental. Hue versus nonhue, light(warm) versus dark (cool), and yellow-green versus yellow-red can berelated to evolutionary processes and, extending Shepard's proposal, canperhaps be viewed as a consequence of human interaction in the three-di-mensionality of our world with its given range of reflectivity of light fromexisting surfaces.

The findings of sex and eye-color differences can also perhaps be givena proximate evolutionary explanation. Women may more often betetrachromatic and see a wider range of the electromagnetic spectrum. Thisdifference between the sexes, perhaps magnified by culture, if our cognitiveresults can be interpreted in this manner, could be due to women, thecollectors, having to recognize many more species during our Pleistoceneevolution than did men, the hunters, who needed attend to only a few.

Eye colors that occur in such intermediate frequencies as in our samplesprobably reflect relatively recent gene flow among previously isolated andmore-homozygous peoples who were formerly more subject to the forcesof genetic drift, or chance, and natural selection. Eye color, determined bypigmentation in the iris, should not affect the spectrum of light received bythe retina. Therefore, we suggest eye color to be a pleiotropic trait, whereone gene has multiple effects. Certainly, additional genetically orientedresearch is necessary to confirm or disprove this speculation. Since cogni-tion is also linked, it could be argued that genes that control eye color alsoaffect cognition. A multicultural study is required to evaluate this conjec-ture. Future studies involving judgments of similarity of color standards,such as the triadic sorting task of the perceptual study reported here, shouldrequire test decisions by subjects to be made in a very brief time space toreduce the chances of the consultant's translating a perception of the colorsof the chips into color names if such studies are to rule out a cognitivecomponent of test performance.

Variation within and across cultures offers a traditional laboratory forexamining these ideas about putative perceptual stages by which thecognition can be constructed. Such a program presents one with a formalmeans of building models that incorporate plausible intermediate forms orprocesses, ones that could be tested in examination of the variety of emer-gent cognitive cultural expressions of the universal foundation upon whichany cognition can be built. Thus perception is a starting point for anyformulation of cognitive universals. This being the case, not only shouldwe consider the limitations that perception places on cognition, but we


should also consider the nature of the constraints that perception places onthe process of building a cultural cognition.

The model that we would propose would feature two kinds of con-straints. One we call a perceptual form constraint; the second, modeled afterShepherd (1994), we call connectedness. The first type constrains the pos-sible candidates for perceptual representation by limiting the level ofabstraction that putative perceptual forms could evince. The second gov-erns the mapping of perceptual structures onto their expressions in thelinguistic and cultural cognitions of the world. It is a hypothesis about howthe cognitive world is constructed upon the perceptual ground.

Notes

Acknowledgments. For their cooperation, the authors thank the three introductoryanthropology classes and their instructors at the University of Missouri, Columbia,that participated in this study, and they thank Stephanie Wilson, who suppliedvaluable bibliographic assistance.

1. An earlier version of this article was presented at the Symposium on Sense andSensibility, organized by Kelly Maynard and N. Louanna Furbee, at the AmericanAnthropological Association Annual Meeting, Atlanta, 1994.

2. These pilot study results have been replicated in a just-completed study of theeffects of sex and eye color on color perception that used a balanced design of 80subjects, 20 each in four cells: brown-eyed men, brown-eyed women, light-eyedmen, and light-eyed women (Furbee et al. n.d.).

3. The coordinates for these 13 standards, based on their locations in the WorldColor Survey version of the Munsell array, were the following: A0, E0, JO, C2, G4,D6, B9, C9, D14, G17, E22, H29, and H33.

References Cited

Benfer, Robert A., Jr., N. Louanna Furbee, and Edward E. Brent, Jr.1996 Expert Systems and the Representation of Knowledge. American Ethnolo-

gist 23:416-420.Berlin, Brent, and Paul Kay

1991 [1969] Basic Color Terms: Their Universality and Evolution. Berkeley: Uni-versity of California Press.

Borgatti, Stephen P.1994 Anthropac 4.0. Columbia, SC: Analytical Technologies.

Dougherty, Janet W. D.1977 Color Categorization in West Futunese: Variability and Change. In So-

ciocultural Dimensions of Language Change. B. G. Blount and M. Sanchez, eds.Pp. 103-118. New York: Academic Press.

Furbee, N. Louanna1992 Effects of Eye Color on Color Perception. Paper presented at the Sympo-

sium on Light on Color Ethnography, American Anthropological AssociationAnnual Meeting, San Francisco.

Furbee, N. Louanna, and Robert A. Benfer, Jr.1983 Cognitive and Geometric Maps: Study of Individual Variation among

Tojolabal Mayans. American Anthropologist 83:305-334.Furbee, N. Louanna, Kelly Maynard, Justin Nolan, Helen Cho, Marsha Quintan,and Robert A. Benfer, Jr.

n.d. Effects of Sex and Eye Color on Color Perception. Unpublished MS.


Harkness, Sara1973 Universal Aspects of Learning Color Codes. Ethos 1:175-200.

Hexing, Ewald1964[1920] Outlines of a Theory of the Light Sense. Lev M. Hurvich and

Dorothea A. Jameson, trans. Cambridge, MA: Harvard University Press.Kay, Paul, and Chad K. McDaniel

1978 The Linguistic Significance of the Meanings of Basic Color Terms. Lan-guage 54:610-646.

Kay, Paul, Brent Berlin, and William R. Merrifield1991 Biocultural Implications of Systems of Color Naming. Journal of Linguistic

Anthropology 1:12-25.MacLaury, Robert E.

1987 Color-Category Evolution and Shuswap Yellow-with-Green. AmericanAnthropologist 89:107-124.

1992 From Brightness to Hue: An Explanatory Model of Color-Category Evolu-tion. Current Anthropology 33:137-186.

MacLaury, Robert E., and Brent Galloway1988 Color Categories and Color Qualifiers in Halkomelem, Salish, Lushoot-

seed, Nooksack, and Yakima. Working Papers of the 23rd Annual Conferenceon Salish and Neighboring Languages, Eugene, Oregon.

MacLennan, Bruce1994 Continuous Symbol Systems: The Logic of Connectionism. In Neural Net-

works for Knowledge Representation and Inference. Daniel S. Levine andManuel Aparicio, eds. Pp. 83-120. Hillsdale, NJ: Lawrence Erlbaum Associates.

McDaniel, Chad K.1972 Hue Perception and Hue Naming. A.B. honors thesis, Harvard College.

Merbs, S. L., and J. Nathans1992 Absorption Spectra of Human Color Pigments. Nature 356:433-^35.

Mervis, C, J. Catlin, and E. Rosen1975 Development of the Structures of Color Categories. Developmental Psy-

chology 11:554-560.Mollon, J.

1992 Worlds of Difference. Nature 356:378-379.Nathans, K.

1991 Molecular-Genetics of Visual Pigments. Journal of General Physiology98:A4-5.

Nathans, K., D. Thomas, and D. S. Hogness1986a Molecular Genetics of Human Color Vision: The Genes Encoding Blue,

Green and Red Pigments. Science 232:193-202.Nathans, J., T. P. Piantanida, R. L. Eddy, T. B. Shows, and D. S. Hogness

1986b Molecular Genetics of Inherited Variation in Human Color Vision. Science232:203-210.

Neitz, M., and J. Neitz1995 Numbers and Ratios of Visual Pigment Genes for Normal Red-Green Color

Vision. Science 267:1013-1016.Neitz, M., J. Neitz, and G.H. Jacobs

1991 Spectral Tuning of Pigments Underlying Red-Green Color Vision. Science252:971-974.

Rosen, E., and C. B. Mervis1975 Family Resemblances: Studies in the Internal Structure of Categories.

Cognitive Psychology 7:573-605.


Rosch, E., C. B. Mervis, W. D. Gray, D. M. Johnson, and P. Boyes-Braem1976 Basic Objects in Natural Categories. Cognitive Psychology 8:382-439.

SAS Institute1992 Chapter 15, The MDS Procedure. In SAS Technical Report P299, SAS/STAT

Software: Changes and Enhancements, Release 6.07. Pp. 249-288. Gary, IN: SASInstitute.

Shepard, R. N.1980 Multidimensional Scaling, Tree-Fitting, and Clustering. Science 210:290-

239.1994 Perceptual-Cognitive Universals as Reflections of the World. Psychonomic

Bulletin and Review 1:2-28.Smith, J. Jerome

1992 Using ANTHROPAC 3.5 and a Spreadsheet to Compute a Free List SalienceIndex. Cultural Anthropology Methods Newsletter 5(3): 1-3.

Smith, J. Jerome, N. Louanna Furbee, Kelly Maynard, Sarah Quick, and Larry Ross1995 Salience Counts: A Domain Analysis of English Color Terms. Journal of

Linguistic Anthropology 5:203-216.Stanlaw, James M.

1987 Color, Culture, and Contact: English Loanwords and Problems of ColorNomenclature in Modern Japanese. Ph.D. dissertation, University of Illinois,Urbana-Champaign.

Swadesh, Morris, and Carl Voegelin1939 A Problem in Phonological Alternation. Language 15:1-10.

Tukane, Y., F. D. Young, and J. de Leeuw1977 Nonmetric Individual Differences Multidimensional Scaling: An Alterna-

tive Least Squares Method with Optimal Scaling Features. Psychometrika42:7-67.

Winderickx, J., D. T. Lindsey, E. Sanocki, D. Y. Teller, A. G. Motulsky, and S. S.Deeb

1992 Polymorphism in Red Photopigment Underlies Variation in Color Match-ing. Nature 356:431-433.

the emergence of color cognition from color perception

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