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
Copyright © 2012 SciRes. 537
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
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
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 &
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
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.
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.
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.
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
Copyright © 2012 SciRes.
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.
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.
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.
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
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.
Percent correct for naming the color of emotion and neutral words
under time pressure.
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
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
Copyright © 2012 SciRes. 539
B. M. BEN-DAVID ET AL.
Copyright © 2012 SciRes.
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.
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
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List of the Words Used in the Study (Translated from
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
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