Open Journal of Depression
2013. Vol.2, No.3, 19-23
Published Online August 2013 in SciRes (
Copyright © 2013 SciRes. 19
Attention Bias to Sad Faces and Images: Which Is Better for
Predicting Depression?
Bita Ajilchi, Vahid Nejati2
1Department of Psychology, Faculty of Human Science, Science and Research Branch University,
Islamic Azad University (IAU), Tehran, Iran
2Department of Psychology, Faculty of Human Science, Shahid Beheshti University, Tehran, Iran
Email: *
Received June 7th, 2013; revised July 7th, 2013; accepted July 15th, 2013
Copyright © 2013 Bita Ajilchi, Vahid Nejati. This is an open access article distributed under the Creative
Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium,
provided the original work is properly cited.
This study aims to compare emotion face and emotion image dot-probe tasks in predicting depression.
The study uses descriptive correlational methods. The subjects studied during the research included the
people between the ages of 19 - 40 years, who visited a particular psychology clinic in Tehran, Iran from
2011 to 2012. The patients studied received a clinical diagnosis, based on an unstructured interview, as
per the 4th Edition of Diagnostic and Statistical Manual of Mental Disorders (DSM-IV), and a screening
test using the Beck Depression Inventory (BDI, cut off point 21 and higher). Then 82 individuals were
selected, using the convenience sampling method. Two computerized dot-probe tasks (emotional faces
and images) were administered to the participants. Pearson’s correlation coefficients and univariate re-
gression analysis showed that, in both tasks, attention bias was significantly linked with depression and
could predict it (P < 0.01). Fisher’s Z-test further showed that the emotion face dot-probe task could pre-
dict depression more precisely than the emotion image dot-probe task (P < 0.01).
Keywords: Attention Bias; Dot-Probe Task; Emotional Face; Emotional Image; Depression
Poor social performance is considered the most recognizable
characteristic of a depressive disorder. (Levendosky, Okun, &
Parker, 1995). Relevant literature indicates that people, who
suffer from depression, fail to establish efficient interpersonal
interactions (Wang, Wang , Chen, Zhu, & Wang, 2008). Thus,
patients with depression have a poor comprehension of social
situations (Beevers, 2009) and they face problems in interpret-
ing interpersonal information, such as emotions and facial ex-
pressions (Bouhuys, Bloem, & Groothuis, 1995). Deficiency in
establishing social interactions plays a key role in the develop-
ment of a depressive disorder (Kerr, Dunbar, & Bentall, 2003;
Inoue, Tonooka, Yamada, & Kanba, 2004, cited in Nejati, Zabi-
hzadeh, Maleki, & Mohseni, 2012). It seems that the cognitive
infrastructures of this vicious circle must be thoroughly inves-
tigated in depressed people. Cognitive theories, relating to de-
pression, (Beck Depression Inventory (BDI), 1976; Teazdale,
1988) say that this disorder of attention bias begins to manifest
itself in the form of depression, in relevant cases. In line with
these theories, several studies showed that depressed people ex-
hibit selective attention towards negative stimuli, even after
their recoveries. (Fritzch et al., 2010; Leung, Lee, Yip, Li, &
Wong, 2009; Staugaard, 2009; Peckman, McHugh, & Otto,
Several researchers have described that this selective atten-
tion, towards sad stimuli, as being neither caused by depression
nor is it considered as a symptom, but rather it plays a major
role in the onset and development of depression. Many resear-
chers discovered that cognitive attention biases towards proc-
essing emotional information, particularly sad stimuli, not only
make the individual vulnerable to depression and cause sus-
tained depressive symptoms, but also that they could develop a
depressive mood, even in those, who have recovered from de-
pression (Beevers & Carver, 2003; Wells & Beevers, 2009).
Baert et al. (2010), Joormann & Gotlibe (2007), Segal, Gemar,
& Williams (1999), Macleod & Mathews (1991), Williams &
Oaksford (1992) and Beck (2008).
The dot-probe task is one of the main tools used in diagnos-
ing of attention bias in depressive disorders. The task, origi-
nally developed by MacLeod, Mathews & Tata (1986), showed
that people respond faster to probes when they are presented
inside the field of awareness rather than outside of it (Chen,
Ehlers, Clark, & Mansell, 2002). Instead of neutral and positive
stimuli, the task makes use of sad and emotional stimuli to di-
agnose attention bias. The nature of the stimuli differs accord-
ing to the nature of the task.
Macleod et al. (1986) originally used words in developing
the dot-probe task, but the procedure was then continued by
Beevers and Carver (2003), Koster, De Raedt, Goeleven, Frank,
& Crombez (2005), Leung et al. (2009) and Baert et al. (2010).
Later, the use of human faces, rather than words, became popu-
lar. The practice was based on the logic that biologically, hu-
man beings may reconstruct emotional facial expressions, even
during a state of unconsciousness. Dimberg, Thunberg, & El-
mehed, 2000; Bradley, Mogg, Falla, & Hamilton (1998) found
that the face indicates real situations better than words do
*Corresponding author.
(Mogg & Bradley, 2002). The face is considered as a social
stimulus that could profoundly affect an attention bias. Fox,
Lester, Russo, Bowles, Pichler, & Dutton (2000), Koster, Ley-
man, Raedt, & Crombez (2006) showed that the face could
transfer much important social and biological information such
as identity, gender, age, emotional state and attractiveness (Cha-
leypanloo, Garoosi Farshi, & Ghenaat Pisheh, 2010).
Koster et al. (2006), Leyman, De Raedt, Schacht, & Koster
(2006), Staugaard (2009) and Fritzch et al. (2010), also used
human faces as stimuli in studying attention bias. The emo-
tional images lately used in dot-probe tasks, instead of words,
showed that this kind of stimuli could create attention bias by
arousing the individual’s selective attention (Schmukle, 2005;
Wells & Beevers, 2009; Sears, Newman, Ference, & Thomas,
2011). Browning, Holmes, Charles, Cowen, & Hamer (2012)
employed two kinds of stimuli, i.e. both words and faces, and
Schmukle (2005) studied word and emotional images as the
stimuli. Compared to normal people, depressed individuals show
a negative attention bias when encountering key social states,
such as facial expressions (Gur, Erwin, Gur, Zwil, Heimberg, &
Kraemer, 1992; Bouhuys, Geerts, & Gordijn, 1999). This atten-
tion bias is linked to increased responses in the nerve network,
which is involved in emotional processing. In comparison with
normal individuals, in depressed people this attention bias is
manifested by increased amygdala responses to negative facial
expressions (scary and sad) (Suslow et al., 2010; Victor et al.,
2010) that could return to a normal response after treatment for
depression (Godlewska, Norbury, Selvaraj, Cowen, & Hamer,
2012). Stuhrmann, Suslow, & Dannloeski (2011), who studied
20 pieces of research on face processes in depressed people, re-
ported disorders in face processing networks that indicated
mood processing bias in amygdala, insula, parahippocampal
gyrus, fusiform, putamen, cingulare and orbitofrontal cortex.
Modinos, Mechelli, Pettersson-Yeo, Allen, McGuire, & Aleman
(2013) found out that in depressed people, the function of brain
areas, related to the emotions, i.e. the inferior frontal gyrus,
including the anterior cingulate cortex, as well as both sides of
the amygdala and insula, are increased to process sad emotional
images. Chechko, Augustin, Zvyagintsev, Schneider, Habel, &
Kellermann (2013) believe that, in depressed people, the cortex
involvement in the lateral prefrontal, parietal and extrastriate is
decreased, in line with an increase in the limbic system (par-
ticularly the right amygdala), when processing emotional faces
and words. At the same time, Kanske, Heissler, Schonfelder, &
Wessa (2012) discovered a decrease in amygdala response to
negative emotional stimuli (not positive) and an increase in the
function of the emotional regulation control network, including
the posterior cingulate and lateral orbitofrontal cortex, while
measuring neural responses to emotional images.
A review of the related literature shows that no research so
far has studied whether attention bias, caused by face and im-
age stimuli, could help in the diagnosis of depression. Some
theoretical arguments show that human emotional faces are
given priority over emotional words, but a few researchers have
compared emotional faces with emotional images. To increase
relevant information and to strengthen its theoretical and re-
search foundations, the current enquiry intends to study the
potential of attention bias as identified by two dot-probe tasks,
using emotional face and emotional image stimuli in the diag-
nosis of depression. The research question is whether the atten-
tion bias identified by emotional face dot-probe tasks differs
from the emotional image dot-probe task in predicting depres-
This study is descriptive and co-relational in its nature. The
subjects of the study included all those people aged 19 - 40 who
had visited a psychology clinic in Tehran from 2011-2012. They
were screened using an unstructured interview as per the 4th
Edition of Diagnostic and Statistical Manual of Mental Disor-
ders (DSMIV-TR), as well as the Beck Depression Inventory
(cut off point of 21 and higher). Finally, eighty-two depressed
patients were selected by means of convenience sampling. The
subjects did two dot-probe tasks, using emotional faces and
emotional images as stimuli.
Beck Depression Inventory (BDI)
This test was developed by Beck and his colleagues. The test
evaluates emotional, motivational, physical and vegetative
symptoms, as well as recognition symptoms. Using the Spear-
man-Brown formula, Beck reported the test’s validity as 0.93.
The questionnaire used has 21 questions, with four multiple an-
swers for each question. The subjects were requested to draw a
circle around the answer that described their feelings best in
that particular week. Fata (1991) has reported the correlation
coefficient between BDI and the Hamilton Depression Test for
Iranian examinees as 0.66. The validity and reliability of the
test in both the healthy and clinical population was proved by a
study conducted in Rouzbeh Hospital, affiliated to Tehran Uni-
versity of Medical Sciences (Kavyani, Mousavi, & Mohit,
Modified Dot-Probe Test of Emotional Faces and
Emotional Images
This is a modified version of the original test (MacLeod,
Mathews, & Tata, 1986) two versions of which were prepared
for this study. In the first version, sad and neutral faces from the
Nim Stim data bank (Tottenham et al., 2009) were used as sti-
muli. The stimuli in the second test consisted of depressive
emotional images, which were selected from the international
emotional images of depression (IAPS, Lang, Bradley & Cuth-
bert, 1995). The images and a star (*) (Figure 1) were pre-
sented in two rectangles that were placed 2 centimeters from
the central fixation point of the monitor. The examinee was
situated 50 centimeters away from the computer.
Figure 1.
Dotprobe task for assessing the attention bias toward two pairs of
Copyright © 2013 SciRes.
Firstly the empty rectangle and the fixation point (+) were
presented for the period of 500 ms. Then two faces were shown
on the left and right hand side of the monitor fixation point, for
a period of 500 ms. The subject had to use the arrows on the
computer keyboard to show the star’s direction. The computer
recorded the response with a reaction time of up to 1 min. The
test was administered via a laptop computer. The total of cor-
rect responses (accuracy) and the average time used for res-
ponding to the questions (reaction time) in each presentation
mode (congruent and incongruent), were calculated separately.
The index of attention bias was calculated by subtracting the
reaction time of the examinees, when the star is directed to-
wards the face, from their reaction time, when the star shows
the incorrect direction.
As observed in Table 1, the attention bias toward the emo-
tional face and the emotional image have a positive significant
relationship with depression (P < 0.01). Thus, univariate re-
gression analysis is presented later to compare the potential of
the above-mentioned dot-probe tasks in predicting depression.
In Table 2, significant F and positive β coefficients show
that the attention bias toward the emotional image could sig-
nificantly predict depression (P < 0.01). The findings suggest
that the high attention bias measured by the emotional image
dot-probe task indicates deeper depression. According to the β
coefficient (β = 0.917) it could be stated that attention bias to-
ward the emotional image determines 84% of the depression
score variance. The regression equation is as follows:
Attention bias = 30.819 + (Attention bias toward emotional
image × 0.798).
In Table 3, a significant F and a positive β show that the at-
tention bias toward the emotional image could significantly
predict depression (P < 0.01). The findings suggest that the
high attention bias measured by the emotional image dot-probe
task indicates deeper depression. According to the β coefficient
(β = 0.785) it could be stated that the attention bias toward the
emotional image determines 62% of the depression score vari-
ance. The regression equation is as follows:
Attention bias = 17.652 + (Attention bias towards the emo-
tional image × 0.440).
To study whether there is a significant difference between
the attention bias index with regard to the emotional face and
Table 1.
Descriptive characteristics and correlation coefficients relevant to de-
pression and attention bias in two dot-probe tasks.
Variable Attention bias Depression
Mean(sd) Face Image FaceImage
Face 6.19(7.33)1 - 0.917*-
Attention bias
index Image 5.33(6.81) - 1 - 0.785*
Face 28.66(7.97)- - 1 -
Image 28.66(7.97)- - - 1
Face 5.33(3.30) - - - -
Reaction time,
congruent Image 7.92(2.10) - - - -
Face 12.39(6.85)- - - -
Reaction time,
incongruent Image 13.25(6.82)- - - -
Note: *P < 0.01.
Table 2.
Variance analysis and regression coefficients to predict attention bias
using the emotional face dot-probe task.
Source Ss Df MS F P<
Regression3919.56 1 3919.56 421.330.0005
Residual744.21 80 9.30
CriterionPredictorConstant B β t P <
bias index
30.820.80 0.92 20.530.0005
Table 3.
Variance analysis and regression coefficient to predict attention bias
using the emotional image dot-probe task
Source Ss Df MS F P<
Regression1407.321 1407.32 128.770.0005
Residual 874.26 80 10.93
Criterion PredictorConstantB β t P<
bias index
17.660.44 0.79 11.350.0005
the emotional image dot-probe tasks, the Fisher’s Z-test was
used. After converting the (r) coefficient scores to (Z) coeffi-
cient scores, the Z Fisher score was 3.19 (Z = 3.19, P =
0.0007). This shows that the difference was significant at the P
< 0.01 level.
The research showed that both dot-probe tasks are signifi-
cantly related to depression, and could even predict it. Com-
pared to the emotional image dot-probe task, the significant Z
Fisher score and the higher correlation coefficient and β co-
efficient in the emotional face dot-probe task indicates that this
task could predict depression more efficiently. This finding is in
line with the following research in terms of the nerve plexus.
Stuhrmann et al. (2011) and Modinos et al. (2013) identified the
relevant areas of the brain involved in processing emotional
faces and images in depressed people. Chechko et al. (2013) show-
ed that in depressed people, the decrease in corticle involve-
ment occurs in line with an increase in the limbic system re-
sponse. Kanske et al. (2012) discovered a decrease in the amyg-
dala response, and an increase in the cortex’s function in proc-
essing emotional images in depressed people.
As earlier stated, attention bias makes the individual vulner-
able to depression, and it also plays the key role in its onset and
development. Thus, both dot-probe tasks used to measure atten-
tion bias could predict depression. On the other hand, depressed
people have problems in processing sad emotional images and
in calling for cognitive control from the higher cortical areas.
This is done in a subliminal way, by the sub-cortical and para-
limbic regions of the brain within the frontal-limbic nerve net-
work (Japee, 2013). Subliminal processing that is independent
of the cognitive analysis is considered a fast procedure. Thus,
depressed people show a faster, more precise attention bias
towards emotional faces (more negative attention bias index).
On the other hand, the more negative attention bias index to-
wards sad faces could indicate a greater degree of depression.
Copyright © 2013 SciRes. 21
Processing sad emotional images takes more time because the
cortical regions are involved, and so thinking and cognitive
analysis have more roles to play in this process. Thus, de-
pressed people show a slower attention bias towards sad images
(more positive attention bias). On the other hand, a more posi-
tive attention bias towards sad images contributes little to the
diagnosis of depression. Thus dot-probe tasks that measure sub-
liminal and unconscious processing (Japee, 2013) could diag-
nose and predict depression more efficiently when using emo-
tional faces as stimuli.
To verify these research findings, one would suggest that fu-
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