The Pale Shades of Emotion: A Signal Detection Theory Analysis of the Emotional Stroop Task

doi:10.4236/psych.2012.37079

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Psychology

2012. Vol.3, No.7, 537-541

Published Online July 2012 in SciRes (http://www.SciRP.org/journal/psych) http://dx.doi.org/10.4236/psych.2012.37079

The Pale Shades of Emotion: A Signal Detection Theory

Analysis of the Emotional Stroop Task

Boaz M. Ben-David1,2,3, Eran Chajut4, Daniel Algom5

1Toronto Rehabilitation Institute, Toronto, Canada

2Department of Speech-Language Pathology, University of Toronto, Toronto, Canada

3Department of Psychology, University of Toronto Mississauga, Mississauga, Canada

4Department of Education and Psychology, The Open University of Israel, Ra’anana, Israel

5Department of Psychology, Tel-Aviv University, Tel-Aviv, Israel

Email: [email protected]

Received April 12th, 2012; revised May 1st, 2012; accepted May 29th, 2012

In the emotional Stroop effect (ESE), people are slower to name the ink color of negative, emotion-laden

words than that of neutral words. Two accounts have been suggested for the ESE, relating it to either de-

ficient attention to color or to temporary disruption of action in the face of threat. Is the ESE driven by a

threat-produced change in perception, or is it a strategic bias in responding? In a pioneer import of Signal

Detection Theory to this realm, threat was found to diminish the psychological distance (d') between the

ink colors, but it did not impact response bias (). The results indicate that the ESE derives from a deep

perceptual change engendered by the negative stimuli and not from changes in the criterion for respond-

ing. These results constrain future theorizing in the domain of emotion-produced changes in behavior, and

provide some support for the threat account of attention under emotion.

Keywords: Emotional Stroop Effect; Attention; Threat; Signal Detection Theory; Emotion

Introduction

Can people focus on an attribute of the stimulus when an-

other attribute is laden with emotion or directly threatening?

There is a voluminous literature concerned with this question

employing mainly the paradigm known as the emotional Stroop

task (e.g., Algom, Chajut, & Lev, 2004; Algom, Zakay, Monar,

& Chajut, 2009; Chajut, Mama, Levi, & Algom, 2010;

McKenna & Sharma, 1995, 2004; Watts, McKenna, Sharrock,

& Trezise, 1986; Williams, Mathews, & MacLeod, 1996). Pre-

sented with words in color, it takes people longer to name the

ink color of emotion or threat words than that of neutral words,

the emotional Stroop effect (ESE). The ESE is a robust phe-

nomenon, yet its source is debated in the literature.

According to the attention account of the ESE (e.g., Wil-

liams et al., 1996), the disproportionate amount of resources

drawn by the emotion words takes a toll on naming their ink

color. It is widely documented that threatening stimuli grab

attention even when the negative information comprises a word

presented in the shielded environment of the laboratory. The

experimental task calls for naming ink colors, yet people cannot

avoid reading the carrier words, emotional and neutral. It is the

extra amount of attention captured by the former that generates

the ESE. According to the threat approach to the ESE, the

menacing content of the word engenders a temporary freeze on

all ongoing activity. The interruption, if for a fraction of a sec-

ond, sustains the prioritizing of resources for efficient action in

the face of (potential) threat (Öhman, Flykt, & Esteves, 2001).

The ESE thus reflects the activity of a general-purpose defense

mechanism that momentarily freezes all activity that is not

directly related to the threat (Algom et al., 2004; Fox, Russo,

Bowles, & Dutton, 2001).

Why are people sluggish to respond to a feature (color) of

emotion stimuli? Are they distracted by the emotion word or

are they paralyzed by its threatening content? Indeed, it may be

the case that both the attention and the threat theories describe

the same phenomenon from different points of vantage (Frings,

Englert, Wentura, & Bermeitinger, 2010). The goal of this

study was to ponder further the nature of the change wrought

about by responding to emotion stimuli. Does the processing of

the threatening content of the word creates a sensory change, or

does it bias the response? In the current study, we elucidate this

issue by harnessing the potent tool of the theory of signal de-

tectability (TSD; Macmillan & Creelman, 2005; cf. Marks &

Algom, 1998).

Applying Detection Theory to the Study of the ESE

Detection theory is a general approach to measuring decision

under uncertainty. In a typical experiment, one of two possible

stimuli (designated, respectively, as signal-and-noise and noise)

is presented and the observer must report on each trial the iden-

tity of the stimulus (= whether or not the signal was presented).

The decision is affected by the sensitivity to the physical dif-

ference separating the stimuli and by the criterion or response

bias adopted, favoring one stimulus over the other in respond-

ing. Detection theory provides distinct procedures to calculate

sensitivity and response bias separately (where each index can

remain invariant in the face of changes in the other). The most

widely used measure to tap sensitivity is d', whereas the most

popular measure to mark bias is . We calculated d' and  for

classification of the ink colors for each participant in each con-

dition of the present study.

In the current adaptation, a word appeared in one of two col-

B. M. BEN-DAVID ET AL.

ors. The participants performed in the routine ESE task, namely,

they identified the ink color of each word. The carrier words—

irrelevant to the task at hand—were negative in one block, but

neutral in another block. A voluminous literature suggests that

the valence of the carrier words modifies performance—the

ESE. What we do not know is the source of this change in per-

formance under emotion or threat. Is it rooted in sensory modi-

fication or in cognitive adjustment? The former would be ex-

pressed in a difference in the values of d' across the emotion

and neutral blocks, the latter in a difference in the pertinent

values of  across the two blocks.

Does Emotion Affect Stimulus Discriminability or

Response Bias?

TSD permits to disentangle effects of perception from those

of response bias—a critical step for understanding behavior

under emotion. Why should threat have an impact on the per-

ception of colors or on the strategy for responding? First, con-

sider the sensory index, d'. If resources are prioritized to deal

with threat, as discussed in the threat account, it comes at the

expense of poorer perception of other attributes, notably that of

the pertinent colors. As a result, perceptual sensitivity for color

can be affected under emotion or threat, so that the ink colors

become psychologically closer to one another. Longer color

naming under emotion (=ESE) ensues.

Consider next the  index, the criterion espoused for report-

ing. Fast and automatic processing of threat can modify the

disposition to respond affirmatively. For example, Windmann

and Krüger (1988) found a bias-induced change in recognition

of emotion words. The authors conclude that “aversive stimulus

valence had affected subjects’ willingness to risk false-positive

responses via automatic and unconscious influences” (p. 625).

More recently, Windmann and Chmielewski (2008) found that

changing the response from affirmative to negative (respond

“yes” or “no” for an “old” item) sufficed to reverse the bias for

detection of threat words (in a memory task). Similar results

were obtained in detection of negative (and neutral) pictures

(e.g., Wiens, Piera, Golkar, & Öhman, 2008) and faces (Wes-

termann & Lincoln, 2010).

Clearly, importing the TSD into the realm of emotion opens

up new avenues for research (in this case, for studying the ESE).

Can it also provide a means for theoretical resolution? It is not

fully clear how to derive the respective predictions by the atten-

tion and the threat accounts with respect to the expected results

of a TSD analysis. Yet, it appears that a change in the sensory

index (d') of TSD across emotion and neutral stimuli is more

closely linked with the threat theory, as this theory entails a

deep perceptual modification under threat. A change in the 

index of TSD, the criterion espoused for reporting, may be

more consistent with the attention theory that does not entail a

genuine perceptual modification in emotion. We admit that

these predictions are rather preliminary and are best considered

as working hypotheses at this point.

Accuracy-Based ESE

Finally, a notable feature of TSD analyses is that they are

based on accuracy or error, not on RT. As a consequence, we

gauged the ESE for accuracy for the first time in the emotion

literature (but see Zeelenberg, Wagenmakers, & Rotteveel,

2006, for a non-ESE study with accuracy). The problem, of

course, is the minuscule rates of errors observed in virtually all

studies of the ESE. How does one generate sufficiently high

rates for error to permit the TSD analysis? Our tactic was two-

fold. First, we imposed a severe time window on responding (cf.

Lindsay & Jacoby, 1994). This encouraged very speedy re-

sponding at the expense of accuracy. Second, we also used

imperfectly discriminable print colors (red and orange). The

two manipulations conspired to produce sufficiently high rates

of error, allowing an accuracy-sustained look at the ESE. In

addition, our task was fashioned so that one font color called

for an affirmation response and the other for a rejection.

Method

Participants

Twenty-eight young adults (between 18 and 26 years of age),

Tel-Aviv University undergraduate students, participated in the

experiment against course credit. All were native speakers of

Hebrew and all had normal or corrected to normal vision (and

color-vision) assessed by self-report.

Stimuli and Apparatus

There were 16 words of various clothing for neutral items

and 16 words associated with terror for negative items (see

Appendix). Note that both types of words were drawn from

single well defined categories, a constraint adopted in order to

rule out any effect of category. The words were equally familiar

based on the average rating of an independent group of 40

Tel-Aviv University students. The students used a scale be-

tween 0 (unfamiliar) and 5 (very familiar) to assess 64 words.

Included in the study were emotion and neutral words with an

average rating between 3 and 4 (inclusive). The two sets of

words were also matched in word length (for a review on the

impact of these lexical characteristics, see Ben-David, Van

Lieshout, & Leszcz, 2011).

The words appeared on the white background of a 17'' color

monitor (set to a resolution of 1024 × 768 pixels). They were

presented at the center of the screen. However, in order to avoid

adaptation and/or strategic responding (e.g., fixating on a small

portion of the print to avoid reading the words when responding

to the color), we introduced a trial-to-trial spatial uncertainty of

15 pixels around the target location. The words were printed in

Arial (Hebrew font, size 48) placed within the invisible frame

of a 118 × 40 pixels rectangle. Viewed from a distance of 60

cm, the word subtended 4.48˚ of visual angle in width and 1.52˚

in height. The words appeared in the prototypical colors of red

or orange (a difference in hue of 15%, based on the software’s

standards) rendering the classification difficult. Each word was

preceded by a row of 7 Xs (black, Arial font size 48) serving as

a mask. We used a loud tone (2000 Hz, 60 dB, 200 ms) to sig-

nal the end of the time window for responding (an error from

the participant’s point of vantage). The tones were played over

a pair of (Peerless) loudspeakers.

Design

The words were presented singly for view. There were two

separate blocks of trials, one entailing the emotion words, and

the other entailing the neutral words (with order counterbal-

anced across participants). Within the block, each word ap-

peared in each of the two ink colors six times, making for 192

538

B. M. BEN-DAVID ET AL.

experimental trials per block. The order of these stimuli was

random and different for each participant. On a trial, the mask

was presented at the center for 50 ms, followed by the word in

color. The time window for responding was set at 500 ms. A

response produced within this limit terminated the presentation

and the mask starting the next trial appeared after 50 ms. How-

ever, if the participant failed to respond during the 500 ms time

window, the presentation terminated with the “error” tone

played aloud. Again, the next trial started after a 50 ms interval.

Procedure

The participant decided whether the ink color was red (“yes”)

or not red (“no”, i.e., orange) by pressing one of a pair of later-

alized keys (A and L; key assignment was counterbalanced

between participants). The participant was asked to do so

within a 500 ms time frame. The participant was further in-

formed that failure to respond within the time limit will be pe-

nalized by an unpleasant tone, and that the trial will be dis-

carded as erroneous. Each block was preceded by 8 training

trials. Unbeknownst to the participant, the first 10 trials in each

experimental block were also considered as practice and dis-

carded form the analysis.

Data Analysis

For purposes of the TSD analysis we considered only the re-

sponses made during the 500 ms interval (88% and 86% in the

emotion and neutral blocks, respectively, t(27) = 1.8, p = .08).

We defined the red color as signal-and-noise (hence, orange as

noise). Consequently, the percentage of correct identification of

red provided the rate of hits (H). In a complementary fashion,

the percentage of incorrect identifications of orange (as red)

provided the rate of false alarms (FA). Based on these rates, we

calculated the sensory index of discriminability (d′ = Z(H) –

Z(FA)) and the decisional index of criterion

( = exp[0.5*((Z(FA))2 – (Z(H))2)]) separately in each block.

Results

The accuracy of identifying color in the blocks with emotion

and neutral words is presented in Figure 1. The first feature to

notice is the unusually high rates of error committed (hovering

at around 37% overall). We conclude that our manipulations

were successful in generating sufficiently high percentage of

errors to allow accuracy based analyses. Note, too, that Figure

1 is the standard ESE plot with the notable exception that accu-

racy replaces RT on the ordinate. Under the inauspicious condi-

tions of the experiment, our participants were more accurate to

detect the ink color of a neutral word (65.9%) than that of an

emotion word (58.6%). This difference favoring neutral words

as carriers of color amounted to an ESE of 7.3% (t(27) = 6.7, p

< .001).

Whence the disruption of performance with negative stimuli

(= ESE)? First consider the data with respect to the sensitivity

of color discrimination presented in the left-hand panel of Fig-

ure 2. The average d' in the block with neutral items (0.869)

was almost twice that in the block with the emotion items

(0.468; t(27) = 6.48 p < .001). Clearly, our participants were

more sensitive to the difference between the same ink colors

when the carrier words were neutral than when the carrier

words were emotional.

70%

60%

50%

Emotion Neutral

Word Type

Accuracy

Figure 1.

Percent correct for naming the color of emotion and neutral words

under time pressure.

1.2

0.8

0.6

0.4

0.2

Emotion Neutral

Sensitivity (d′)

Word Type

Emotion Neutral

1.2

0.8

0.6

0.4

0.2

Critertion (β)

(a) (b)

Figure 2.

Results of the TSD analysis. Panel A: Average values of perceptual

discrimination, d', for ink color of emotion and neutral words. Panel B:

Average values of response bias, , for ink color of emotion and neutral

words. Error bars represent one standard error around the mean.

Finally, consider the data with respect to response bias in the

right-hand panel of Figure 2. We did not discern any consistent

pattern of the values of  across the two blocks. The net result

of this unsystematic variability was that the mean values in the

two blocks were almost fully comparable (at around 1.09). We

conclude that the response criterion adopted by the participants

was not modified by stimulus valence. The difference in out-

come between the d' and the  was further supported by the

interaction of word valence and TSD measure (F(1,27) = 32.2,

p < .001, MSE = 0.035, 2



= .55).

Discussion

This early foray into TSD based emotion research already

yielded important results. They show that the content of the

word exerts a deep sensory effect on the processing of its ink

color. The presence of threat in the form of a negative or emo-

tional word diminishes the psychological distance separating

the ink colors of the carrier words. In general, people are de-

sensitized to the differences between stimulus attributes that are

unrelated to the threat attribute. In contrast, response bias is not

altered by threat. The upshot is that the ESE derives from per-

ceptual changes in the environment engendered by the presence

of threat. The slowdown with emotion items is the toll exacted

on performance by the (temporarily) dilapidated perception. In

B. M. BEN-DAVID ET AL.

540

other words, threat-related cost also entails poorer discrimina-

tion of stimulus attributes.

The results mandate the conclusion that the ESE is the out-

come of an instinctive perceptual-motor reaction to threat. The

presence of threat engenders a wholesale regrouping of the

organism’s resources in order to deal effectively with the situa-

tion. Resources are allocated to the threat attribute at the ex-

pense of other attributes. Perception becomes thus blunt for

attributes other than the threat one. This finding is consistent

with recent results from our laboratory showing that non-target

attributes often do not undergo semantic processing in the

presence of emotion or threat (Chajut, Schupak, & Algom,

2010). The findings are also consistent with those by Zeelen-

berg et al. (2006) and by Schupp, Junghofere, Weike, and

Hamm (2003), which implicate a perceptual source for changes

in performance under emotion. Taken together, these results

provide further support for the threat account of the ESE, where

the sluggish performance (otherwise termed “temporary freez-

ing”) in the face of threat is the cost of reshuffling of priorities.

Incidental support for this conclusion comes from a pair of

recent studies on the classic Stroop effect that manipulated

color (actually, the discriminability of the ink colors) in a direct

fashion. Ben-David and Schneider (2009, 2010; see also

Ben-David, Nguyen, & Van Lieshout, 2011) found that the

content of the word exerted a greater influence on color naming

(thereby generating a larger Stroop effect) when the colors were

less salient. Within the framework of the ESE, the natural sali-

ence of a threat stimulus combines with poorer color perception

(itself produced by the threat) to generate slower color naming.

In conclusion, let us issue a caveat with respect to the general

impact of the current results. First, they must be replicated and

extended to further stimuli, populations, and areas of stress and

anxiety. Second, the null-effect with respect to response bias

derives from large unexplained variability. It would be salutary

to replicate it in the face of reduced variance. Nevertheless, our

data constrain future theories of the ESE, challenging any a

strategy-driven source for the effect.

Acknowledgements

The first author was partially supported by a grant from the

Ontario Neurotrauma Foundation (2008-ABI-PDF-659). We

wish to thank Noa Calderon for her assistance in collecting the

data.

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Appendix

List of the Words Used in the Study (Translated from

Hebrew)

Neutral words: Scarf, Hat, Glove, Shirt, Pants, Coat, Sweater,

Umbrella, Vest, Boot, Dress, Skirt, Tie, Sandal, Sock and Shoe.

Emotion words: Murder, Suicide, Terrorist, Danger, Atrocious,

Extermination, Death, War, Suffocation, Injured Person (a

single word in Hebrew), Horror, Poison, Terrorist Attack (a

single word in Hebrew, lexically unrelated to Terrorist), Burn,

Mucus, and Scare.

The Original Hebrew Words

Neutral words:,ףיעצ,עבוכ,הפפכ,הצלוח,םייסנכמ,ליעמ,דווסררהירטמ

לברס,ףגמ,הלמש,יאצחת,הבינע,לדנס,.ברג, לענ

Emotion words:חצר,דבאתמ,לבחמ,הנכס,העווז,הדמשה,תוומ,המחלמ,קנח,

עוצפ,המיא,לער,עוגיפ,היווכ,הלגומ,הלהב .