Aveneu Park, Starling, Australia

Threat-Related to pose a threat to the

 

 

 

 

Threat-Related Stimuli in Visual Search

Bodine
Gonggrijp

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Emma
de Heus

Marieke
Schutte

Bram
Zwanenburg

Vrije
Universiteit Amsterdam

Supervisor:
Vasiliki Kentrou

15-12-2017

Abstract

Reward-related
stimuli??1  are known to be able to automatically capture visual
attention. The attentional prioritisation of rewarded-stimuli may have served
as an evolutionary advantage to increase the chances of survival in humans.
Threat-related stimuli are assumed to be able to automatically capture visual
attention as well, because the automatic detection of threat-related stimuli
should also pose an evolutionary advantage. The literature still seems to be
inconclusive about the ability of threat-related stimuli to automatically
capture visual attention. Many studies used stimuli however that did not
genuinely seem to pose a threat to the participants. Threat-related stimuli are
able to automatically capture attention when directly threatening stimuli were
used (Schmidt, Belopolsky & Theeuwes; 2015). In this study a fear-conditioning design,
in which a neutral stimulus was paired to an electric shock, and a visual search
paradigm were used to investigate whether the findings of Schmidt, Belopolsky
and Theeuwes could be replicated??2 . It was hypothesized that the presence of
threat-related distractors is more impairing to goal directed behavior in
visual search than neutral distractors. No differences were found between the
participants’ average reaction times to find the targets in both distractor
conditions (neutral vs threat), suggesting that the ability of threat-related
stimuli to automatically capture attention is still debatable??3 .

 

 

Threat-Related
Stimuli in Visual Search

            Stimuli that
signal??4  a
probability of receiving a reward are known to be able to automatically capture
visual attention, even when they are not task relevant or when they are
unobtrusive (Anderson, 2017). The influence of reward-related stimuli on the
visual attention system has been investigated in multiple studies. Anderson,
Laurent and Yantis (2011) for example found that reward-related stimuli were
more distracting in a visual search task than stimuli that were unrelated to a
reward. In addition, Hickey, Chelazzi and Theeuwes (2010) found that stimuli
that previously predicted a high value reward seemed to capture visual
attention faster than stimuli that predicted a low value reward??5 .                                         Attention
can be either top-down or bottom-up. Top-down attention is a voluntary and goal
directed attentional shift, whereas bottom-up attention is an involuntary,
reflexive attentional shift in reaction to physical stimuli in the environment.
Attentional capture represents the reflexive attentional shift (Schmidt,
Belopolsky & Theeuwes, 2015).             Various
brain regions with an attentional prioritisation of reward-related stimuli have
been mapped out, including the intraparietal sulcus, the lateral occipital
complex, the early visual cortex and the caudate tail. These brain regions are
referred to as the `value-driven attention network’. The presentation of
previously reward-related stimuli have been associated with elevated activity
in the value-driven attention network, leading to an attentional bias
(Anderson, 2017).                                                                                                        The attentional bias towards
reward-related stimuli amongst other stimuli in the environment may have served
as an evolutionary advantage. Allocation of attention towards reward-related
stimuli may increase the odds to detect possible future gains that increase the
chances of survival (Schultz, 2004). Emotional stimuli are assumed to be
prioritised by the visual attention system in a similar way as reward-related
stimuli, because an attentional bias towards emotional stimuli may have served
as an evolutionary advantage to increase the chances of survival as well.
(LeDoux, 1996). Fear seems to be critical for survival. Fear can be defined as
an anticipated response that is elicited by a stimulus that is associated with
an unpleasant or dangerous outcome. The human brain contains a fear circuit
which mainly relies on the limbic structures and is able to automatically
detect potentially harmful and/or dangerous stimuli such as spiders and snakes.
Automatic detection of threatening stimuli may enable humans to quickly (and adequately)
respond to these stimuli to increase the chances of survival (e.g., by avoiding
a venomous snake) (Öhnman & Mineka, 2003; Schmidt, Belopolsky &
Theeuwes, 2015).                                                                                                        The
effects of threatening (i.e., potentially dangerous or painful) stimuli on the
visual attention system have been investigated in multiple studies. In these
studies, both threat-related pictures and neutral pictures were shown to
participants to compare if threat-related pictures received more priority of
the visual attention system than neutral pictures. The results emanating from
these studies were contradictory, which suggests that the effects of
threatening stimuli on the visual attention system are still inconclusive
(Devue, Belopolsky & Theeuwes, 2011; Ohman, Flykt & Esteves, 2001). The
above
mentioned studies ??6 however used
stimuli that were not directly threatening for the participants, which could
have led to an underestimation of the effects of threatening stimuli on the
visual attention system. It may therefore be useful to create threatening
stimuli that pose a more genuine risk for participants. This can be achieved by
using a fear-conditioning design. Conditioning refers to the process in which
the association of two unrelated stimuli is learned. In a fear conditioning
design, a neutral stimulus (CS) is paired to an unconditioned stimulus (US)
with an aversive outcome, while another CS remains neutral (CS-). The CS that
is paired with the US becomes a (salient) aversive stimulus (CS+). The CS+ and
CS- can be used as distractors, and can be compared by using a visual search
paradigm to investigate whether the CS+ distractor is prioritised over the CS-
distractor by the visual attention system (Schmidt, Belopolsky & Theeuwes,
2015).         The fear design was used by
Schmidt, Belopolsky and Theeuwes (2015) to pair a CS to an electric shock
(creating a CS+ distractor). Another CS remained unpaired (CS- distractor).
Subsequently, a visual search paradigm was used to investigate whether the
presence of the CS+ distractor amongst other distractors would slow target
search more than when the CS- distractor was presented amongst other
distractors. Evidence was found that the presence of a CS+ distractor did slow
down target search more than the presence of a CS- distractor. Based on the
results it was concluded that threat-related stimuli are able to automatically
capture attention.                                                                                                     In
this study the fear-conditioning design was adopted to investigate whether the
findings of the above mentioned study (i.e., that threat-related stimuli are
able to capture attention) could be replicated by using a similar research set
up, in order to expand the literature about attentional capture by
threat-related stimuli. Based on the results of Schmidt, Belopolsky and
Theeuwes (2015), it was hypothesized that the presence of threat-related
distractors is more impairing to goal directed behaviour than the presence of
neutral distractors. Based on the hypothesis it was expected that the average
reaction times of participants to find targets in visual search would be
significantly higher when the distractors included a CS+ compared to when a CS-
was included. 

Method

Participants

            The
sample comprised 15 participants (… male and … female) with
reported normal or corrected-to-normal vision. The participants’ ages ranged
from … to … years (M
= …, SD = …). All
participants were recruited at the Vrije Universiteit Amsterdam (VU) and
received either cash or course credits in return of participation. The Vaste
Commissie Wetenschap en Ethiek (VCWE) of the VU granted ethical approval to
carry out the experiment.

Apparatus and materials

The experiment was run in a sound-attenuated and
dimly-lit cubicle at the social sciences laboratory of the VU. A Digitimer DS7A
constant current stimulator (Hertfordshire, UK), with two electrocardiogram
electrodes attached to it, was used to create electric shocks. The electrodes
were applied over the tibial nerve of the participants’ left ankle. Two
substances were used to optimize transmission of the shocks: SignaGel was
applied in the electrodes to increase the conduction of the electrical signal
and Nuprep was used to clean the participants’ ankle and therefore decrease
impedance of the skin.                                                    OpenSesame
was used to create and conduct the visual search paradigm. The visual stimuli
were presented against a grey background on a 22
inch monitor with a resolution of 1024×768 pixels and a 120Hz refresh rate.
Participants had to place their chins on a chinrest which was positioned at a
distance of 70 cm from the monitor. The paradigm contained two phases: a
conditioning phase and an experimental phase. The two stimuli in the
conditioning phase were a green and a blue circle with a visual angle of 0.79°. The stimuli in the
experimental phase were nine individual coloured circles with a visual angle of
1.32°. Eight of these
stimuli were equidistantly represented in an imaginary circle around a fixation
point in the centre of the screen. The colours of these stimuli were green,
blue, red, orange, brown, yellow, pink and white. The penwidth of the stimuli
in both the conditioning and the experimental phase was 12 pixels. Inside the
target stimulus a black line was presented that was either horizontally or
vertically directed. Inside the other stimuli (i.e., the distractors) a tilted
black line was presented. The line inside the distractors had a visual angle of
0.32° and was randomly
tilted in an orientation of 22.5°,
45° or 67.5°.

 

 

Procedure     

            Prior to the experiment
the participants received a brief instruction about the experiment and signed
an informed consent form. Hereafter the electrodes were applied to the
participants’ left ankle. The shock intensity was then calibrated in a way that
the shock would be “annoying but painless” for each participant. The
participants received sample shocks and were asked to rate if these shocks were
annoying or painful on a 5-point scale (i.e., 1 = very mild, 2 = mild, 3 =
annoying, 4 = quite annoying, 5 = painful). The calibration started with an
intensity of 16 mA. The intensity of the shocks was then increased until the
participants rated 4 (“quite annoying, but painless”) on two consecutive trials
or until the maximum intensity of 45 mA was reached. The maximum intensity
would be used throughout the experiment if it was reached during the
calibration procedure.                                                                                     After the calibration procedure the
participants received brief instructions about the conditioning phase. The
conditioning phase consisted 108 trials. During
the conditioning phase two stimuli, 54 green circles and 54 blue circles, were
presented individually in a random order for 2000 ms per stimulus, with an interval of … ms between the presentation of each
stimulus. Between the presentation of each stimulus, the participants
had to focus on a fixation dot to keep attentive. One of the two stimuli
signalled a one-third probability of receiving
a shock in the last 20 ms of the stimulus presentation (i.e., CS+), whereas the
other stimulus was neutral (i.e., CS-). The colour associated with threat was
counterbalanced. This meant that for half the participants the green stimulus became
the CS+ and the blue stimulus the CS-, and for the other half the CS+ and CS-
were reversed. Which colour was associated with the shock was mentioned in the
instruction prior to the conditioning phase. The participants did not need to
respond to the stimuli during the conditioning phase. After the conditioning
phase the participants were asked what colour was associated with the shock to
check if they learned the CS-US contingency. Furthermore, the participants received
a brief instruction about the experimental phase.                                                                                            The
experimental phase consisted of one practice block including 12 trials and
eight blocks including 60 trials. As mentioned
in the instructions the participants no longer received shocks during the
experimental phase. During the experimental phase the participants had to
visually search and respond to a target stimulus that was surrounded by
distractors, including either the CS+ or CS- amongst the distractors. The
target could pop up at any of the nine stimulus locations with an equal
probability. The participants had to press the “z” key when the target stimulus
contained a horizontal line and the “/” key when the target stimulus contained
a vertical line. Prior to the task the participants were instructed to respond
as fast as possible. After finishing the experiment the participants received a
debriefing form wherein the goal of the experiment was explained. The e-mail
address of the main researcher was given in case the participants had any
further questions.

Results

            Prior
to the data analysis all outliers were removed from the dataset. All trials
with incorrect responses and reaction times that were more than two standard
deviations above the mean reaction time were defined as outliers, as well as
data with an accuracy below 80%. The removal of outliers led to a loss of 10%
of the data. The participants’ reaction times to find the target in both
distractor conditions are summarized in table 1. As shown in table 1, the mean
reaction times slightly differed between the CS- and CS+ condition. The
reaction times to find the target in the CS- condition were slightly higher
than in the CS+ condition. This difference however was not found to be
significant, as revealed by a one-way Analysis of Variance (ANOVA), F(1,6650) = .02, p = .895. Another ANOVA was conducted to investigate whether the
distractor colours had an effect on the reaction times when controlled for
distractor type (i.e., CS+ or CS-). No evidence was found for an effect of
distractor colour, F(1,1) = .02, p = .881.                  

Table 1
Summary of the Reaction Times to find
Target when Neutral and Threat-Related Stimuli are Presented

Distractor Type                                   Reaction
time (ms)                                          Trials
(N)

                                                            M                     SD

CS-                                                      1451.29           266.46                                     3341

CS+                                                     1450.42           268.44                                     3309

Total                                                    1450.85           267.43                                     6650

 

 

Discussion

            The
aim of this study was to investigate whether previous findings of the ability
of threat-related stimuli to capture attention, could be replicated (Schmidt,
Belopolsky & Theeuwes, 2015). It was hypothesized that the presence of
threat-related distractors is more impairing to goal directed behaviour than
the presence of neutral distractors. There was no difference found between the
average reaction times to find targets in the CS- and CS+ distractor
conditions, implying no support for the hypothesis.                                                              The results
of this study do not seem to be in line with the findings of Schmidt,
Belopolsky and Theeuwes (2015). There are some possible explanations for the
difference in findings that can be considered. The first possible explanation
is that the visual search paradigm used in this study was more difficult. For
instance, the average reaction times of the participants to find the targets
were much higher than expected, which may be related to the targets’ identity.
Whereas Schmidt, Belopolsky and Theeuwes (2015) for example used targets that
were merely identifiable by shape, this study used targets that had a similar
shape and colour as the distractors, possibly making them harder to identify
and thus leading to higher average reaction times. The higher average reaction
times may have made it harder to detect the effects of the CS+ distractor in
this study. Another possible explanation for the differences in findings was
that the CS+ was not strongly enough associated with an electric shock.
Firstly, participants in this study were informed that they would not receive
electric shocks during the experimental phase. The knowledge of not receiving
electric shocks anymore may have caused the participants to be less
apprehensive for the CS+ during the experimental phase. As a result, the CS+
distractor may have been no more salient than the CS- distractor during the
experimental phase, ending up in similar reaction times to find the target in
both conditions. Secondly, the majority (two-third) of the CSs in the
conditioning phase did not end up in receiving an electric shock. Receiving
electric shocks in response to the majority of the CS presentations (e.g.,
two-third of the time) could have made the CS+ more salient and therefore more
distractive during the experimental phase. This could possibly have led to
higher reaction times to find the targets in the CS+ condition.                         The above mentioned
factors may pose a limitation for this study, because they may have caused
higher average reaction times and an attenuated effect of the CS+ distractor. A
few implications for future research can therefore be considered. Future
studies could use a visual search paradigm with targets that share fewer
characteristics with the distractors. Furthermore, studies could shorten the
conditioning phase to make sure that participants receive an electric shock (or
any other aversive outcome) the majority of the time when the CS is presented.
Finally, future studies could keep the participants uninformed concerning
whether they will or will not receive electric shocks during the experimental
phase.                       The results
of this study seem to suggest that the presence of threat-related distractors
is not more impairing to goal directed behaviour than the presence of neutral
distractors. The previous findings that threat-related stimuli are able to
automatically capture attention may therefore be debatable. Further research
may be necessary to explore the topic of the effects on threat-related stimuli
on (visual) attention and subsequently broaden the literature.

References

Anderson, B. A. (2017). Reward processing in the value-driven attention
network:

reward signals tracking cue identity and location. Social cognitive and
affective neuroscience, 12(3), 461-467.

Anderson, B. A., Laurent, P. A., & Yantis, S.
(2011). Learned value magnifies salience-based

attentional capture. PLoS One, 6(11),
e27926.

Devue, C., Belopolsky, A. V., & Theeuwes, J.
(2011). The role of fear and expectancies in

capture of covert attention by spiders. Emotion,
11(4), 768.

LeDoux, J. E. (1996). The emotional brain. New York,
NY: Simon & Schuster.

Hickey, C., Chelazzi, L., & Theeuwes, J. (2010).
Reward changes salience in human vision

via the anterior cingulate. Journal of Neuroscience,
30(33), 11096-11103.

Öhman, A., Flykt, A., & Esteves, F. (2001).
Emotion drives attention: detecting the

snake in the grass. Journal of experimental
psychology: general, 130(3), 466.

Öhman, A., & Mineka, S. (2003). The malicious serpent: Snakes as a
prototypical stimulus

for an evolved module of fear. Current directions in psychological
science, 12(1), 5-9.

Schmidt, L. J., Belopolsky, A. V., & Theeuwes, J.
(2015). Attentional capture by

signals of threat. Cognition and emotion, 29(4),
687-694.
Schultz,
W. (2004). Neural coding of
basic reward terms of animal learning theory, game

theory: microeconomics and behavioral ecology. Current Opinion Neurobiology, 14

(2004), pp. 139-147.

 

 

 ??1It’s good to include some literature about reward-related attentional
capture in the introduction, but maybe it would be better to limit the Abstract
to the focus of this study, which is fear-driven capture.

 

Perhaps you could start with mentioning
value-driven attentional capture (which includes cases of both reward and
punishment), and then after that place the sentence about threat-related
stimuli that you’ve already written!

 ??2Ask them to describe this better:

 

Maybe it would be better to devote more
space in describing the methodology in more detail, rather than in describing both
reward- and fear-driven attentional capture.

 

Also: Try to devote some space to
mentrion exactly what your design was: What statistical test did you conduct?
What are your variables of interest that you included in the model?

 ??3Perhaps it would be a good idea to give a brief – perhaps one small
sentence – overview of what you’ve included in your discussion

 ??4In general, it’s a good idea to begin the introduction with a general paragraph
which gives an outline of the rest of the introduction. In other words, it
might be a good idea to have your first paragraph be a brief summary of the
points that you will cover in the rest of the Intro, leading up to the aim of
the present study and a very brief mention of your hypothesis.

 ??5Here, it might be a good idea to state the aim of the present study and/or
the hypothesis, so that the reader knows what to expect going into the
introduction.

 ??6In order to give the reader an overview of the methodolody used to
study our research question in the existing literature, it might be a good idea
to decribe a few studies looking into effects of threatening stimuli. What was
their design? What methodologies did they use? What did they conclude?

x

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