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Paranormal and Religious Believers Are More Prone to Illusory Face Perception than Skeptics and Non-believers

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Illusory face perception, a tendency to find human-like faces where none are actually present in, for example, artifacts or scenery, is a common phenomenon that occasionally enters the public eye. We used two tests (N = 47) to analyze the relationship between paranormal and religious beliefs and illusory face perception. In a detection task, the participants detected face-like features from pictures of scenery and landscapes with and without face-like areas and, in a rating task, evaluated the face-likeness and emotionality of these areas. Believer groups were better at identifying the previously defined face-like regions in the images but were also prone to false alarms. Signal detection analysis revealed that believers had more liberal answering criteria than skeptics, but the actual detection sensitivity did not differ. The paranormal believers also evaluated the artifact faces as more face-like and emotional than the skeptics, and a similar trend was found between religious and non-religious people. Copyright © 2012 John Wiley & Sons, Ltd.
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Paranormal and Religious Believers Are More Prone to Illusory Face Perception than
Skeptics and Non-believers
TAPANI RIEKKI*, MARJAANA LINDEMAN, MARJA ALENEFF, ANNI HALME and
ANTTI NUORTIMO
Institute of Behavioural Sciences, Division of Cognitive Psychology and Neuropsychology, University of Helsinki, Helsinki, Finland
Summary: Illusory face perception, a tendency to nd human-like faces where none are actually present in, for example, artifacts
or scenery, is a common phenomenon that occasionally enters the public eye. We used two tests (N = 47) to analyze the relationship
between paranormal and religious beliefs and illusory face perception. In a detection task, the participants detected face-like
features from pictures of scenery and landscapes with and without face-like areas and, in a rating task, evaluated the face-likeness
and emotionality of these areas. Believer groups were better at identifying the previously dened face-like regions in the images
but were also prone to false alarms. Signal detection analysis revealed that believers had more liberal answering criteria
than skeptics, but the actual detection sensitivity did not differ. The paranormal believers also evaluated the artifact faces
as more face-like and emotional than the skeptics, and a similar trend was found between religious and non-religious people.
Copyright © 2012 John Wiley & Sons, Ltd.
INTRODUCTION
Everysooften,peopleclaimtond the face or gure of a
religious character or other important person in peculiar
places, for example, on toasted bread. These ndings are
even reported in the news, and the items are sold on eBay.
Although most of us can identify the shapes claimed,
reactions vary from serious wonder about the supposed
miracle to ignorance of these gures and disbelief in their
importance. These intriguing, funny, and often surprising
perceptions of human shapes can happen in unexpected
situations and have even ended up in a scientic journal, in
the case of the face of a sick man peering out of an ultrasound
image (Roberts & Touma, 2011). The present study examines
the role that religious and other paranormal beliefs may play
in illusory face detection.
Research on reports of seeing a face where no face
actually exists is scarce. In a recent study, illusory face
detection was found to be relatively high even in pure noise
images, with face detection rates as high as 41% (Rieth, Lee,
Lui, Tian, & Huber, 2011). The same study also suggested
that illusory face perception is highly affected by top-down
processes (i.e., expectations and previous experiences),
not only by bottom-up processes, such as visual input. In
another study, two participants tried to detect smiles on
faces with mouth areas consisting of white noise (Gosselin
& Schyns, 2003). Illusory detection varied from relatively
low to high: from 7% to 48%. These studies suggest that
even when only noise is present, false perceptions of faces
or facial parts are common.
Krummenacher, Mohr, Haker, and Brugger (2010) showed
that people who believe in paranormal phenomena errone-
ously identied faces in scrambled congurations more
often than skeptics did. Other studies have also shown that
paranormal believers are prone to perceive meaningful
patterns in ambiguous stimuli in, for example, semantic or
visual tasks (Brugger et al., 1993; Giannotti, Mohr, Pizzagalli,
Lehman, & Brugger, 2001). It can thus be expected that
illusory face recognition is more typical for paranormal
believers than for skeptics.
Illusory face detection can be considered, in a liberal sense,
as a form of anthropomorphism. Anthropomorphism, in a
strict sense, denotes the belief that nonhuman phenomena
have uniquely human properties, such as a sense of humor.
However, nowadays the concept is often used more liberally
in connection with attributes that may apply to animals
as well (e.g., a belief that God is an intentional agent;
Boyer, 1996) or without an assumption of a genuine belief
(My computer is grouchy today).
Cognitive scientists of religion have suggested that
anthropomorphism explains peoples inclination to believe in
gods (Barrett, 2000; Guthrie, 1993). The few available studies
about the relationship between individual anthropomorphism
and religiosity surprisingly propose that this is not the case.
Shtulman (2008) found that the more a person believed in
a supernatural being, the less it was described with such
human attributes as awake, honest, talkative, and skinny.
Similarly, perceiving such properties as anger, maliciousness,
wisdom, and self-condence in pictures of a tree and a volcano
is not connected to religious beliefs but rather to other
paranormal beliefs (Norenzayan, Hanse, & Cady, 2008).
Anthropomorphism is characterized as a process where the
highly accessible, early developing, and fundamental
knowledge about human agents serves as an inductive base
that is applied to nonhuman targets (Epley, Waytz, &
Cacioppo, 2007; Guthrie, 1993). Therefore, it is possible that
an association between religiosity and anthropomorphism is
more apparent in basic social processes functional early in
development and crucial in dealing with other people, such
as face detection (Beauchamp & Anderson, 2010), than in
less fundamental and later developing human attributes such
as talkativeness and self-condence.
We examined illusory face detection with artifact face
pictures and non-face pictures. Artifact face pictures are
pictures of artifacts and scenes in which face-like features
*Correspondence to: Tapani Riekki, Institute of Behavioral Sciences, Division
of Cognitive Psychology and Neuropsychology, P.O. Box 9, 00014 University
of Helsinki, Finland.
E-mail: tapani.riekki@helsinki.
Copyright © 2012 John Wiley & Sons, Ltd.
Applied Cognitive Psychology,Appl. Cognit. Psychol. (2012)
Published online in Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/acp.2874
such as eyes and a mouth might be perceived even though the
picture includes no actual faces or people. The hypotheses
were tested with two tasks: the perception of human faces in
artifacts and the rating of the face-likeness and emotionality
of the faces. Two hypotheses were set: (1) paranormal
believers and religious people are more prone to illusory
face perception than skeptics and non-religious people are
and (2) paranormal believers and religious people rate
artifact faces as more face-like and emotional than skeptics
and non-religious people do.
METHOD
Participants
A total of 47 (26 women, 21 men, mean age = 31 years,
range 2050 years) healthy participants with normal or
corrected to normal vision were included in the study. The
participants were recruited from various electronic mailing
lists (e.g., university studentslists), internet forums (e.g., a
skeptics association), notice boards (e.g., at an esoteric
bookstore), and with the snowball method. The participants
had 29 different occupations, and 39% of them either
were university students or university graduates. To obtain
participants from the opposite ends of the paranormal
beliefs continuum, two different advertisements were used.
These were otherwise identical, but in the rst advertisement
we emphasized that we are looking for participants who view
the paranormal positively or believe that there is an invisible
spiritual world; in the other, we stated that we were looking
for participants who are skeptical about the existence of
paranormal phenomena. The participants received personal
feedback from a questionnaire about their thinking style as
a reward. We also asked the participants whether they were
familiar with the idea of artifact faces and if they had, for
example, visited internet pages dedicated to the phenomena.
Familiarity did not predict performance in any of the tasks
(all ps>.50).
Originally 73 people were recruited for the study. The distri-
bution of paranormal and religious beliefs was found to be
strongly skewed, which was probably due to the emphasis
on skepticism or paranormal beliefs in the recruitment process.
Only those belonging to the upper and lower quartiles (25%)
were included in the analyses: paranormal believers (N=19,
mean age = 34 years) and skeptics (N= 20, mean age = 28
years); religious people (N= 20, mean age =34 years) and
non-religious people (N= 19, mean age = 27 years). We
focused on the more extreme groups to avoid a possible
qualitative difference between mild and strong believers:
believers who hold mild or medium strength beliefs may be
habitual believers, not true believers or skeptics (Vyse,
1997). Paranormal beliefs and religiousness correlated
strongly with each other, r= .84, p<.001, and 30 participants
who were categorized either as paranormal believers or as
skeptics were also categorized as religious and non-religious,
respectively. Thus, even though we speak separately about
paranormal and religious believers (or skeptics and non-
believers), the groups overlapped.
Religious and paranormal beliefs were assessed with
Tobacyks (2004) Revised Paranormal Belief Scale. The
scale includes 26 items. The four items that measure
traditional religious beliefs (e.g., I believe in God) were used
to measure religiosity (Cronbachsa= .85). Twenty items
addressing beliefs in psi, superstition, spiritualism, extraor-
dinary life forms, and precognition were used to measure
non-religious paranormal beliefs (a= .96; e.g., Astrology
is a way to accurately predict the future,Apersons
thoughts can inuence the movement of a physical object).
The questions were answered with a ve-point scale
(1 = strongly disagree,5=strongly agree). Two items
concerning the possibility of extraterrestrial life and witches
were removed because several participants reported
interpreting them in a non-paranormal way. The questionnaire
was completed after the experimental part of the study. Prior to
the experiment, the participants signed an informed consent
form and were given a short brieng about the study, including
information regarding ethical issues and the ow of the study.
A longer description of the study was given at the end.
Stimuli
The stimuli pictures were chosen in several steps. First,
28 color photographs were chosen from existing private
photographs of the authors that t the requirements for the
stimuli. Then, we took additional photographs to complete
a set of 150 color photographs of artifact faces and 100
non-face pictures. All of the artifact face pictures had a
face-like area where, at the minimum, eyes and a mouth
could be perceived. The faces in the pictures were evenly
distributed to different areas of the photographs. Some
of the artifact pictures were staged, such as ofce tools
arranged on a table, whereas others were natural, such as
a rock wall. The pictures depicted items, objects, and places
such as furniture, rooms, buildings, and landscapes. No
humans or animals were in the pictures. When possible,
the artifact face picture had a control non-face picture
with the same setting, theme, and light, taken by the same
camera (see Figure 1 for examples). In the non-face
pictures, there were no face-like areas. To keep the pictures
as natural as possible, they were not converted or adjusted
in any way except for resizing them to 640 640 pixels.
Next, four people rated whether they were able to detect
faces in the artifact face pictures and in the non-face pictures.
If three raters agreed upon the same face area, the picture
was added to the artifact face set. Also, to dene the artifact
face areas in the pictures, all of the raters estimated the oppo-
site top and bottom corners of the perceived face area, and
the box calculated from the average of these values was then
used as a hit box area for the face in the detection task. If any
of the raters reported a face-like area in a non-face picture,
the picture was discarded. A total of 124 artifact face pictures
and 99 non-face pictures were chosen to pilot the study.
A pilot test with 10 participants (mean age 32 years, seven
women) was conducted to test and choose the pictures for
the main study. Half of the participants took the test in a
laboratory and the rest with a laptop computer in various
places using the same procedure as in the main study, which
is described in the succeeding text. Thirty-eight pictures in
which everyone had perceived an artifact face were excluded
along with one picture in which no one had perceived a face.
T. Riekki et al.
Copyright © 2012 John Wiley & Sons, Ltd. Appl. Cognit. Psychol. (2012)
Twelve non-face pictures were rejected because of ambiguities.
The rest of the 98 artifact face pictures were used in the
detection and rating task along with the 87 non-face pictures
in the detection task.
The detection task
The detection task was done in a dimmed laboratory with a PC
and a Samsung 22" 1440x 900 LCD screen. The stimuli were
presented with Neurobehavioral Systems Inc.sPRESENTATION
W
14.1 software. The participants sat 60 cm from the screen.
The viewing angle was not restricted, and answering was
done with a mouse. The background color of the screen
was gray throughout the study.
The participants read the instructions for the study from a
computer screen. The test started with practice sections that
taught the answering method and the idea of artifact faces.
Because of the rapid pace of the test, participants were
instructed to be fast but as precise as possible. The rst
practice section consisted of six small green squares. The
participants had to point to each square and click on it as
quickly and precisely as possible, after which the next one
would be shown. In the second part, the six squares were
shown again but now only for 1000 ms each, and the
participants had to point to and click on the area in which
they had seen the square.
In the third section, six artifact faces and two non-face
pictures were used. To exemplify a range of artifact faces,
pictures were chosen from the pilot study on the basis of their
relative difculty, from easy to difcult. The participants were
instructed to try to nd a face-like area in the pictures. If
they found one, they were to point with the mouse to the
approximate location of the middle of the face, that is, the
nose, and press the left mouse button. If there was no
face-like area, they were instructed to press the right mouse
button. The answering time was not restricted, and the
pictures were presented one by one. To give feedback to
the participants, the target picture was presented again after
every answer, for both right and wrong answers, with the
face-like area circled or with an X in the middle of the picture
for non-face pictures. The fourth practice section used the
same procedure and instructions as the main task, which is
described next, but like the third section had only two
non-face pictures and six artifact face pictures.
In the main experiment, the participants were instructed to
try to nd face-like areas from randomly shown 98 artifact
face pictures and 87 non-face pictures. If they found one, they
were to point with the mouse to the approximate location of
the middle of the face and press the left mouse button. If there
was no face-like area, they were instructed to press the right
mouse button. The main task proceeded in the following
way. First, a xation cross was shown for 1000 ms. Second,
a picture was shown for 1000 ms. Third, a mouse cursor
appeared on the screen to be used for answering with an
answering time of 4000 ms. Because the pictures were
smaller than the whole screen, mouse clicks were made
on a highlighted gray area that replaced the area of the
pictures, as the picture was not shown during the time given
for answering. After the answer was given or if the participant
did not answer within the given answering time, the test
continued automatically to the next xation cross.
The variables for the hit and miss rates for the artifact
faces and non-face pictures were calculated in the following
way. For the artifact faces, left mouse clicks (yes, there is a
face-like area in the picture) were coded as hits if the answer
was given in the previously dened face area of the picture,
and all right clicks (no, there is no face-like area) were
coded as misses. If the area clicked when answering yes
was outside the previously dened face area, the answer
was coded as yes-miss. For the non-face pictures, all left
mouse clicks (yes) were coded as false alarms and right
mouse clicks (no)ascorrect rejections. Non-responses
for both types of pictures were coded as non-responses
(no group differences were found, both ps>.249). The
internal consistency of the test was good for both the artifact
faces (a= .93) and the non-face pictures (a= .98).
Figure 1. Artifact faces. Two pictures of artifact faces (rst row) and control pictures (second row)
Illusory faces and paranormal beliefs
Copyright © 2012 John Wiley & Sons, Ltd. Appl. Cognit. Psychol. (2012)
The rating task
In the rating task, presented after a short break following the
detection task, the participants rated the face-likeness and
emotionality of the artifact face pictures using a visual analog
scale and a mouse. The instruction was as follows: Next you
will be shown pictures in which a face-like area can or cannot
be found. Rate the possible face-like areas using the following
scales.The participants were asked to indicate how face-like
the artifact face was (the left end of the scale = not at all,
coded as 0; the right end = alot, coded as 170) and how
emotional the face was (the left end = negative, coded
as 170; the middle = no emotion, coded as 0; the right
end = positive, coded as 170). To obtain a score for the
perceived strength of the emotion, only the absolute value of
the rating was used (0170). Answering was done by moving
the cursor along the visual analogical scale and pressing the
left mouse button. If the participant thought that there was
no face-like area in the picture, they were instructed to press
the right button (this answer was coded as 0). The rst picture
was a practice picture taken from the detection taskspractice
section and was not used in the analyses. The artifact face
pictures and the setting were the same as in the detection task.
The pictures were presented randomly, without a time limit,
one by one with the answering scale and the question. Two
variables, face-likeness (a=.98) and emotionality (a= .95),
were formed from the ratings.
RESULTS
We used signal detection analysis (Green & Swets, 1966;
Macmillan & Creelman, 2005) to analyze the results of the
detection task because it enables the correction of the hit
rate with the false-alarm rate, revealing actual detection
sensitivity. Yesanswers for artifact faces and false-alarm
rates for non-face pictures were calculated and used to
calculate two variables based on signal detection analysis:
sensitivity d0(perceptual sensitivity) and the criterion C
(bias towards the answer yes). For all means, see Table 1.
Analyses of variances and covariance were conducted
between the paranormal believers and skeptics and the
religious and non-religious people between all the variables.
Age was added as a covariate in the analysis because
the paranormal believers were older than the skeptics,
F(1,37) = 6.45, p= .015,
p
2
= .148, the religious people
were older than the non-religious, F(1,37) = 10.01,
p= .003,
p
2
= .213, and because age correlated with
misses for artifact faces in the fast-paced detection task,
r= .24, p= .044.
The religious people had more false alarms in non-face
pictures, F(1,36) = 6.34, p= .016,
p
2
= .150, but also
more hits in predetermined face areas in artifact face pictures,
F(1,36) = 10.15, p=.003,
p
2
= .220, than the non-religious
people had. Similarly, the paranormal believers had more
false alarms in non-face pictures, F(1,36) = 7.95, p= .008,
p
2
= .181, and more hits in the predetermined artifact face
areas, F(1,36) = 9.99, p=.003,
p
2
= .217, than the skeptics
had. Regarding sensitivity d0, neither the comparison between
the paranormal believers and skeptics nor the comparison
between the religious and non-religious people was statistically
signicant (both p0s>.225). There were, however, group
differences in response criterion C. The paranormal
believers had a lower criterion than the skeptics had,
F(1,36) = 11.02, p= .002,
p
2
= .234, and the religious believers
lower than the non-religious people, F(1,36) = 6.06, p= .019,
p
2
= .144. No group difference was found in the yes-miss
answers, between the religious and non-religious people,
F(1,36) = 2.93, p= .095,
p
2
= .075, nor between the paranormal
believers and the skeptics, F(1,36) = 2.10, p= .156,
p
2
= .055.
Age had a signicant independent effect on the response
criterion and hit rate; the older participants had less hits and a
lower criterion value than the younger participants had in
both group comparisons between the believer groups.
Between the religious and non-religious people, the group
differences were not statistically signicant without
controlling for age. Regarding the paranormal believers
and skeptics, all statistically signicant differences were also
signicant without controlling for age, except for the hit rate
on artifact faces.
To approximate whether the believer groups were better
than non-believers at identifying the previously dened
face-like regions in the images, analyses of covariance were
conducted with age as a covariate. The number of correct
location identications divided by the sum of correct and
incorrect location identications for all trials where
participants reported detecting a face was the dependent vari-
able. The results showed that paranormal believers scored higher
(M= 90) than skeptics did (M=87), F(1,36) = 6.01, p= .019,
p
2
= .143, and that religious people scored higher (M= 90)
than non-religious people did (M= 86), F(1,36) = 5.26,
p= .028,
p
2
= .127.
In the rating task, the paranormal believers rated the
artifact faces as more face-like, F(1,37) = 6.25, p=.017,
p
2
= .145, and emotional, F(1,37) = 4.70, p= .037,
p
2
= .113,
Table 1. Means and standard deviations of all variables in the different groups
Paranormal
believers Skeptics
Religious
believers
Non-religious
people
Hit rates in predetermined artifact face areas 0.52 (0.13) 0.46 (0.12) 0.51 (0.12) 0.48 (0.12)
Yes-miss answers given outside the predetermined artifact face areas 0.05 (0.03) 0.07 (0.05) 0.06 (0.03) 0.08 (0.06)
False alarms for non-face pictures 0.16 (0.10) 0.10 (0.07) 0.15 (0.10) 0.10 (0.07)
Correct rejections for non-face pictures 0.84 (0.10) 0.90 (0.07) 0.85 (0.10) 0.90 (0.07)
Sensitivity d01.30 (0.38) 1.45 (0.31) 1.33 (0.36) 1.33 (0.36)
Response criterion C0.43 (0.34) 0.67 (0.39) 0.47 (0.34) 0.62 (0.38)
Face-likeness in the rating task 110 (50) 72 (44) 101 (51) 79 (39)
Emotionality in the rating task 54 (18) 42 (14) 51 (18) 45 (15)
T. Riekki et al.
Copyright © 2012 John Wiley & Sons, Ltd. Appl. Cognit. Psychol. (2012)
than the skeptics did. In contrast, the religious people
and non-religious people rated the face-likeness of the
pictures equally, F(1,37) = 2.29, p= .139,
p
2
= .058, and
no difference was found for emotionality ratings either,
F(1,37) = 1.03, p=.318,
p
2
= .027.
DISCUSSION
The religious people saw artifact faces in pictures of, for
example, rocks, landscapes, and lifeless material objects more
often than the non-religious people did. Similarly, the people
who believed in other paranormal phenomena (e.g., astrology
and telepathy) detected faces in the artifacts more often than
the skeptics did. Supporting Hypothesis 2, the paranormal
believers also regarded these face-like areas as more face-like
than the skeptics did and assigned more extreme emotions to
them. A similar trend was found between the religious and
non-religious people, but the differences were not signicant.
Moreover, compared with the non-believers and skeptics, the
religious and paranormal believers not only detected faces
more often when they were actually present, but in line with
Hypothesis 1, they also saw more faces in pictures without
any face-like patterns.
Signal detection analysis revealed that the participant
groups did not differ in their sensitivity in detecting faces
but that the paranormal and religious believers had a reduced
criterion for approving the presence of a face, reected in the
low number of misses at the expense of high false alarm
rates. The believerstendency to report seeing faces regard-
less of whether there were faces or not implies that they were
susceptible to the suggestion that faces may be present, on
the basis of, for example, a yea-sayingtendency, the
priming effect of the practice items, or on a conrmation bias,
which has been shown to be common among paranormal
believers (Hergovich, 2003; Wiseman, Greening, &
Smith, 2003). As such, the results are in line with earlier
ndings that paranormal believers are more prone to nd
patterns in noisy or ambiguous stimuli than other people
are (e.g., Brugger et al., 1993; Giannotti et al., 2001; Krum-
menacher et al., 2010) and that paranormal beliefs are asso-
ciated with a tendency to jump to conclusions on the basis
of inadequate evidence (Blagrove, French, & Jones, 2006;
Brugger & Graves, 1997).
However, it might be possible that the results are not only
due to these factors alone because the way in which the
paranormal and religious believers detected faces was not
indiscriminate. Whereas in a typical signal detection design,
the participants are simply asked to answer yes or no, in the
present study they also had to point to the area where the face
was. Interestingly, the paranormal and religious believers
were more likely to nd the face-like areas than the skeptics
and non-believers were: the group differences that were
found were in these hits, not in the yes answers given outside
the predetermined face areas. However, it is possible that the
believer groups identied the location of more faces simply
because they had the opportunity to do so as they reported
detecting faces overall more than non-believers. Therefore,
in future studies, believersdetection of face-like pictures
should be tested with a design where participants are always
asked to make location responses.
As a whole, the results hint at the possibility that the
believers may be overly sensitive to social information and
that only a small amount of information is sufcient to
activate their social information processing. This possibility
would be consistent with the arguments that these beliefs,
like anthropomorphism, stem from the capacity to recognize
and understand human beings (Epley et al., 2007). Theoretical
arguments (e.g., Bering, 2006; Bloom, 2007; Kelemen, 2004)
and empirical ndings (e.g., Lindeman & Aarnio, 2007;
Lindeman et al., 2008; Svedholm, Lindeman, & Lipsanen,
2010) suggest that paranormal and religious believers
stretch universally and early developing human attributes,
such as beliefs, desires, and intentional purpose, to inappro-
priate realms. It has also been suggested that processing
information relating to human beings is a fundamental
dimension of domain-specic cognition that comes in degrees
in the general population, ranging from underdeveloped
to hyperdeveloped (i.e., exaggerated) social cognition
(e.g., Baron-Cohen, Knickmeyer, & Belmonte, 2005;
Crespi & Badcock, 2008). Considering the theoretically
plausible link between social information processing skills
and paranormal and religious beliefs, it could be useful to
study their association more closely in future studies.
In the introduction, we suggested that detecting faces
in artifacts with no face-like patterns is one form of
anthropomorphism. For the present, theoretical arguments
have mostly focused on anthropomorphism as a determinant
of belief in gods and other spirits (Barrett, 2000; Guthrie,
1993), but empirical ndings have been rare and inconclusive
(e.g., Norenzayan et al., 2008; Shtulman, 2008), most
probably because of the myriad of ways the concept of
anthropomorphism can be operationalized. Our results
suggest that both religiosity and paranormal beliefs are
associated with anthropomorphism and that the tendency
to attribute human qualities to nonhuman phenomena may
extend to face perception as well.
Illusory face perception, a phenomenon often in the
public eye, was here studied with as natural stimuli as
possible, which has advantages and disadvantages. The
pictures were chosen for their naturalness to ensure face
validity: we tried to use stimuli as close to real-life situa-
tions as possible. On the other hand, this limits control over
the images. For example, a more controlled psychophysical
approach with an equal number of non-face and face
pictures could be used to investigate more precisely
where the group differences lie at the perceptional level.
Using receiver operating characteristics (see, for example,
Macmillan & Creelman, 2005) could further highlight the
relation of sensitivity and the response criterion. Also, to
rule out a possible response bias in the rating task, a control
condition of non-face pictures could be used. It should also
be noted that the paranormal believers were here partly
the same participants as the religious individuals (or the
skeptics and non-religious participants, respectively), and
it could be useful to use more diverse groups of paranormal
and religious believers in the future.
One thing that we learned during the research was that
illusory face perception is a pervasive phenomenon. It was
Illusory faces and paranormal beliefs
Copyright © 2012 John Wiley & Sons, Ltd. Appl. Cognit. Psychol. (2012)
hard to nd pictures of artifact faces that were difcult
enough to detect but still realistic because most of the faces
were so self-evident. Thus, the line between when a pattern
is face-like and when it is not is challenging to draw, and
as our results show, that line may be in a different place
for different individuals. To conclude, we may all be biased
to perceive human characteristics where none exist, but
religious and paranormal believers perceive them even more
than do others.
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... Previous studies investigating the relationship between paranormal beliefs and perceptual processing under conditions of high visual noise stimuli has yielded diverse outcomes 5,8,15,[18][19][20] . Blackmore and Moore 8 found that individuals who believe in the paranormal are more likely to identify patterns in ambiguous or noisy visual stimuli, often resulting in incorrect recognitions and frequent misidenti cations in everyday life. ...
... Lastly, Van Elk 15 showed that paranormal beliefs are related to a bias in detecting agency, even in stimuli with low ambiguity, highlighting a tendency to attribute intentionality where none exists. These studies suggest that paranormal beliefs are associated with heightened sensitivity to ambiguity and a tendency to nd patterns and meaning where there may be none, using signal detection paradigm, 5,8,15,[18][19][20] . However, it remains uncertain whether this bias is domain-general (i.e., a tendency to a rmatively respond) or domain-speci c stimulus categories, particularly towards speci c types of stimuli. ...
... A total of 82 healthy right-handed (Edinburgh Handedness Inventory score ranges: 40-100, consisting of 51 males and 31 females) students were selected for the study based on previous studies 15,20,34 . We were looking for students who believed in or were skeptical about paranormal beliefs. ...
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Previous research has shown a connection between paranormal beliefs and a tendency to attribute meaning to ambiguous stimuli in signal detection paradigms. However, whether this bias is general or specific to certain stimulus categories remains unclear. To address this issue, we used a face/house categorization task to investigate how paranormal believers and skeptics perceive human agents versus non-natural objects amidst varying levels of visual noise. Our behavioral data, along with drift-diffusion modeling (DDM), revealed that paranormal believers outperformed skeptics in categorizing ambiguous stimuli, including both faces and houses. This study highlights the impact of belief systems on perceptual and visual processing.
... This cognitive bias, wherein individuals tend to discern meaningful patterns within uncertain perceptual backgrounds, forms the basis for the development of paranormal and conspiracy beliefs [9,17]. Previous research has confirmed that individuals who embrace conspiracy beliefs often rely on unreliable information when making decisions and exhibit a tendency to identify patterns within insignificant sensory stimuli [9,[18][19][20][21][22]. Believers in conspiracy theories have also displayed a propensity for incorrectly identifying faces within chaotic patterns, interpreting ambiguous motion presentations as involving human agents, and attributing face-like qualities to images of environments [19,23,24]. Despite extensive investigations into cognitive biases and their association with belief in conspiracy theories, the underlying neural mechanisms remain inadequately understood. ...
... As expected, the distribution of belief in conspiracy theory was not evenly distributed. Based on previous studies [23,46], participants in the upper and lower 30% of the belief spectrum were included in the analysis, which comprised of believers (n = 18; 18 male; mean age (SD) = 27.66 (8.55); mean CTQ score = 53.88, SD = 3.51) and skeptics (n = 17; 9 male, 8 female; mean age (SD) = 25.47 (7.50); mean CTQ score = 36.64, ...
... The study aimed to investigate how resting-state EEG activity affects the perceptual decision-making abilities of believers in conspiracy theories who tend to perceive meaningful patterns in noise [6][7][8][9][10][11][12][18][19][20][21][22][23][24]. This study investigated associations between resting EEG oscillations, endorsement of conspiracy beliefs, and performance on a visual pattern recognition task requiring the identification of faces and houses embedded in visual noise. ...
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Prior beliefs, such as conspiracy beliefs, significantly influence our perception of the natural world. However, the brain activity associated with perceptual decision-making in conspiracy beliefs is not well understood. To shed light on this topic, we conducted a study examining the EEG activity of believers, and skeptics during resting state with perceptual decision-making task. Our study shows that conspiracy beliefs are related to the reduced power of beta frequency band. Furthermore, skeptics tended to misclassify ambiguous face stimuli as houses more frequently than believers. These results help to explain the differences in brain activity between believers and skeptics, especially in how conspiracy beliefs impact the categorization of ambiguous stimuli.
... (for the correlation between the Paranormal beliefs scale and the Walking Man Test based on stimuli containing 96 distractors, in a sample of paranormal fair visitors; Van Elk, 2013), with most of them being between r = .20 and r = .35. Because of this, apophenia is frequently hypothesized to be a cognitive mechanism that influences and sustains the expression of PLEBs phenomena (Blain et al., 2020;Fyfe et al., 2008;Grant et al., 2014;Mamiya et al., 2016;Reed et al., 2008;Riekki et al., 2013;Tsakanikos, 2006;Van Elk, 2013). However, the other part of Blain et al.'s claimthat apophenia indicates an openness to implausible patterns and is thus related to Pure Openness (Blain et al., 2020, p. 281)is empirically questionable. ...
... We used Noise Pareidolia and Walking Man tests because they were specifically created to assess apophenic tendencies and thus validated as appropriate measures of apophenia (Mamiya et al., 2016;Van Elk, 2013). However, although Snowy Picture Taks and the Moving Triangles Test were respectively created to assess object perception and mentalization, tasks like these are the most widely used indicators of apophenia in the field (e.g., Hartmann & Müller, 2023;Riekki et al., 2013;Van Elk, 2013;Walker et al., 2019;Whitson & Galinsky, 2008). These tasks have face validity: False positives on these tasks represent products of hyperconstructing and attributing meaning, rather than deficits in other cognitive processes like perception, attention, and inhibition. ...
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... In order to test the hypothesis that supernatural beliefs are linked to agency detection (e.g., Nieuwboer et al., 2014;Riekki et al., 2013;Riekki et al., 2014;Tratner et al., 2018;van Elk, 2013;van Elk et al., 2016), we performed the same linear mixed effect regression as in the main analysis, but this time adding mean scores on the PSBS scale as additional predictor and its interaction with the other factors. We started with preprocessing the questionnaire data and excluding 4 participants with missing responses (no participant failed the attention check). ...
... Contrary to frequent claims that individual differences in agency detection are related to supernatural beliefs (e.g., van Elk, 2013; Tratner et al., 2020), we did not find evidence for this relationship. This null finding adds to the literature, in which some studies reported a relationship between agency detection and supernatural beliefs (Riekki et al., 2013;van Elk, 2013;Nieuwboer et al., 2014), and some failed to provide evidence (e.g., Tratner et al., 2020) or found mixed results (van Elk et al., 2016). Note that based on the predictive processing account, there is no reason a priori why supernatural beliefs should be related to agency detection, though we speculate that some forms of beliefs could motivate believers to look for more patterns in ambiguous data (see, e.g., Nees and Phillips, 2015;Van Prooijen et al., 2017;Narmashiri et al., 2023) thus increasing the prior probability assigned to hypotheses involving agents. ...
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The phenomenon of "hearing voices" can be found not only in psychotic disorders, but also in the general population, with individuals across cultures reporting auditory perceptions of supernatural beings. In our preregistered study, we investigated a possible mechanism of such experiences, grounded in the predictive processing model of agency detection. We predicted that in a signal detection task, expecting less or more voices than actually present would drive the response bias toward a more conservative and liberal response strategy, respectively. Moreover, we hypothesized that including sensory noise would enhance these expectancy effects. In line with our predictions, the findings show that detection of voices relies on expectations and that this effect is especially pronounced in the case of unreliable sensory data. As such, the study contributes to our understanding of the predictive processes in hearing and the building blocks of voice hearing experiences.
... Darkness causes fear and anxiety because brains are hardwired to expect sensory stimulation and will do their best to work out a coherent representation even from imperfect input by filling in the missing details based on experience and memory. This explains why we perceive crooked trees in a dark forest as monsters or mistake a piece of an old garment in the attic to a supernatural being (Riekki et al. 2013). These misperceptions are based on our experiences and memory, and the brain uses various top-down mechanisms for filling in the gap. ...
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This article covers the neurobiological and psychological aspects of horror movies. Cinema audiences are not exposed to real threats, thus the movie should pass the brain's “reality check” systems and emotion regulation to engage the fear responses. This is achieved through vicarious simulation, proximity of threats, and unpredictability of the fearful events, and using universal sources of fear such as illness or isolation. Paradoxical appeal of horror movies stems from universal curiosity toward morbid and threatening subjects, mixing of emotions of fear and excitement in the brain, and the capability to learn about dangerous situations safely in the context of movies. These findings are summarized in a conceptual model for eliciting fear through cinema.
... Specifically, many studies have investigated correlates of paranormal beliefs in the domain of cognitive functioning and personality characteristics. For instance, a wide variety of cognitive biases and reasoning errors have been associated with an increased tendency to believe in paranormal phenomena, ranging from agency detection biases [13][14][15], the illusion of control [11,[16][17][18] and the self-attribution bias [19], to ontological confusions [10,[20][21][22][23], illusory pattern perception [24][25][26][27] and jumping to conclusions [16,28,29]. Relatedly, a tendency to apply less stringent criteria for 'evidence' has been related to an increased likelihood to endorse paranormal beliefs; paranormal believers may be more likely to endorse many different statements, especially in the face of ambiguous information. ...
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Paranormal beliefs encompass a wide variety of phenomena, including the existence of supernatural entities such as ghosts and witches, as well as extraordinary human abilities such as telepathy and clairvoyance. In the current study, we used a nationally representative sample ( N = 2534 ) to investigate the presence and correlates of paranormal beliefs among the secular Dutch population. The results indicated that most single paranormal phenomena (e.g. belief in clairvoyance) are endorsed by 10–20% of Dutch respondents; however, 55.6% of respondents qualify as paranormal believers based on the preregistered criterion that they believe in at least one phenomenon with considerable certainty. In addition, we invited four analysis teams with different methodological expertise to assess the structure of paranormal beliefs using traditional factor analysis, network analysis, Bayesian network analysis and latent class analysis (LCA). The teams’ analyses indicated adequate fit of a four-factor structure reported in a 1985 study, but also emphasized different conclusions across techniques; network analyses showed evidence against strong connectedness within most clusters, and suggested a five-cluster structure. The application of various analytic techniques painted a nuanced picture of paranormal beliefs and believers in The Netherlands and suggests that despite increased secularization, subgroups of the general population still believe in paranormal phenomena.
... With regard to DU, our results suggest that differences in social perception between people who believe and do not believe in DU should be interpreted with care, as they might also reflect more general differences in the pattern detection (e.g., Peng et al., 2022). With regard to illusory pattern perception, our results echo previous studies showing a relationship between paranormal beliefs and illusory pattern perception (Krummenacher et al., 2010;Riekki et al., 2013;van Elk, 2013) and show that this relationship can be extended to related beliefs such as the belief in DU. ...
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A recent study suggested that belief in dualism (DU) is related to basic social cognitive processes, such as detecting biological motion in noisy displays. However, dualistic beliefs are strongly related to paranormal beliefs, which are also correlated with biological motion perception. The question thus arises whether the previously found relationship between belief in DU and biological motion perception can be explained by paranormal beliefs and whether this relationship is unique to biological motion or reflects a more general tendency to see patterns in noise. We used signal detection theory to measure participants’ ability to discriminate biological motion (Experiments 1 and 3) and random dot motion (Experiment 2) from scrambled background noise. Furthermore, the Free Will Inventory was used to measure the strength of three free will (FW)-related beliefs: belief in FW, belief in determinism (DE), and belief in DU. The Revised Paranormal Belief Scale (RPBS) was used to measure the strength of paranormal beliefs. Across the three experiments (N = 1,028), the results revealed that belief in DU correlated negatively with perceptual sensitivity and correlated positively with false alarm rate in both the biological motion and the random dot motion task. In addition, paranormal belief was found to explain the relationship between belief in DU and biological motion perception. The findings of this study suggest that correlations between belief in DU and biological motion perception are best explained in terms of a more general relationship between belief in DU and (illusory) pattern recognition.
... In particular, magical thinking was the subscale of the SPQ that was most strongly expressed in the believers' group. Magical thinking is connected with increased susceptibility to psychosis, 56 antiscientific attitudes, 57 illusory perception, [58][59][60] and it is genetically connected to schizophrenia. 61 Crucially, participants with higher magical ideation tend to rely on a limited amount of objective evidence to construct meaningful models, which are also overestimated, 62 and showed decreased activity in the cognitive evaluation network during the processing of evidence that contradicts a belief. ...
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In recent years, several studies have found that conspiracy believers tend to be more susceptible to cognitive biases (e.g., conjunction fallacy, proportionality bias, agency detection bias, etc.). The aim of this work is to review such literature, systematizing these concepts in a unifying framework of conspiracy mentality as a set of biased cognitive processes, which categorizes cognitive biases in two classes: those that contribute to belief formation and those that contribute to belief updating. Drawing on several empirical results, this paper summarizes the role of cognitive biases in conspiratorial thinking, offering some insights for future research and raising questions about the possible weaknesses of this approach.
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We all live in a world of uncertainty — in some cases, the most critical events in our lives are completely unpredictable and utterly unexpected. Many people respond to this uncertainty with superstitious beliefs or actions— from carrying good luck charms to knocking on wood or crossing fingers. But even though our understanding or the natural world tells us that these signs and gestures cannot possibly affect the events at which they are directed, superstition is still extremely common, if not universal, among people of all occupations and every educational and income level. Why is superstitious behaviour so prevalent? How is this behaviour established and maintained? Is there a superstitious personality? These are just some of the questions addressed by Stuart Vyse in Believing in Magic. To answer these questions, Vyse examines current behavioural research and show us that every day superstitions are the natural result of several well-understood psychological processes. Written in a style that is both entertaining and informative, this book demonstrates how complex—even paradoxical—human behaviour can be understood through scientific investigation. It addresses the personality features associated with superstition and the roles of operant conditioning, reasoning errors, and social influence in the development of superstitious beliefs and actions. In addition, children;s superstitions and the relationship of superstition to psychopathology are discussed. Although superstition is a normal part of human behaviour, Vyse agrues that we must provide alternative methods of coping with life;s uncertainties by teaching decision analysis, promoting science education, and challenging students to critically evaluate the sources of their beliefs.
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Detection Theory is an introduction to one of the most important tools for analysis of data where choices must be made and performance is not perfect. Originally developed for evaluation of electronic detection, detection theory was adopted by psychologists as a way to understand sensory decision making, then embraced by students of human memory. It has since been utilized in areas as diverse as animal behavior and X-ray diagnosis. This book covers the basic principles of detection theory, with separate initial chapters on measuring detection and evaluating decision criteria. Some other features include: complete tools for application, including flowcharts, tables, pointers, and software;. student-friendly language;. complete coverage of content area, including both one-dimensional and multidimensional models;. separate, systematic coverage of sensitivity and response bias measurement;. integrated treatment of threshold and nonparametric approaches;. an organized, tutorial level introduction to multidimensional detection theory;. popular discrimination paradigms presented as applications of multidimensional detection theory; and. a new chapter on ideal observers and an updated chapter on adaptive threshold measurement. This up-to-date summary of signal detection theory is both a self-contained reference work for users and a readable text for graduate students and other researchers learning the material either in courses or on their own. © 2005 by Lawrence Erlbaum Associates, Inc. All rights reserved.