Download Comparison of visual perceptual organization in schizophrenia and body dysmorphic disorder

Psychiatry Research 229 (2015) 426–433
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Psychiatry Research
journal homepage: www.elsevier.com/locate/psychres
Comparison of visual perceptual organization in schizophrenia and
body dysmorphic disorder
Steven M. Silverstein a,n, Corinna M. Elliott b, Jamie D. Feusner c, Brian P. Keane a,
Deepthi Mikkilineni a, Natasha Hansen b, Andrea Hartmann b, Sabine Wilhelm b
a
Department of Psychiatry and University Behavioral Health Care, Rutgers University, 151 Centennial Avenue, Piscataway, NJ 08854, USA
Department of Psychiatry, Massachusetts General Hospital/Harvard Medical School, Boston, MA, USA
c
Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at University of California-Los Angeles, Los Angeles, CA, USA
b
art ic l e i nf o
a b s t r a c t
Article history:
Received 13 September 2014
Received in revised form
5 May 2015
Accepted 17 May 2015
Available online 27 June 2015
People with schizophrenia are impaired at organizing potentially ambiguous visual information into
well-formed shape and object representations. This perceptual organization (PO) impairment has not
been found in other psychiatric disorders. However, recent data on body dysmorphic disorder (BDD),
suggest that BDD may also be characterized by reduced PO. Similarities between these groups could have
implications for understanding the RDoC dimension of visual perception in psychopathology, and for
modeling symptom formation across these two conditions. We compared patients with SCZ (n ¼ 24) to
those with BDD (n ¼ 20), as well as control groups of obsessive–compulsive disorder (OCD) patients
(n ¼20) and healthy controls (n ¼20), on two measures of PO that have been reliably associated with
schizophrenia-related performance impairment. On both the contour integration and Ebbinghaus illusion tests, only the SCZ group demonstrated abnormal performance relative to controls; the BDD group
performed similarly to the OCD and CON groups. In addition, on both tasks, the SCZ group performed
more abnormally than the BDD group. Overall, these data suggest that PO reductions observed in SCZ are
not present in BDD. Visual processing impairments in BDD may arise instead from other perceptual
disturbances or attentional biases related to emotional factors.
& 2015 Elsevier Ireland Ltd. All rights reserved.
Keywords:
Schizophrenia
Body dysmorphic disorder
Perception
Vision
Perceptual organization
Obsessive–Compulsive Disorder
RDoC
1. Introduction
It is increasingly recognized that there is overlap between
certain psychiatric syndromes in terms of their genetic, neurobiological, cognitive, behavioral, and phenomenological characteristics (Guilmatre et al., 2009; Bellivier et al., 2013; Doherty
and Owen, 2014; Monzani et al., 2014). The mounting evidence for
this conclusion has led the National Institute of Mental Health
(NIMH) to introduce the Research Domain Criteria (RDoC) initiative (Cuthbert and Insel, 2010; Insel et al., 2010). The rationale
behind RDoC is that diagnosis and treatment of mental disorders
should not be driven primarily by a focus on signs and symptoms
(given their problems with reliability and various forms of validity), but rather, by a focus on dimensions of functioning with
known pathophysiological mechanisms. A related implication of
RDoC is that the yield of psychopathology research may be more
fruitful if studies examine these dimensions across current diagnostic categories. One RDoC dimension that has been studied
n
Corresponding author.
E-mail address: [email protected] (S.M. Silverstein).
http://dx.doi.org/10.1016/j.psychres.2015.05.107
0165-1781/& 2015 Elsevier Ireland Ltd. All rights reserved.
repeatedly within diagnostic categories is cognition, a subcategory
of which is perception.
A well-documented visual impairment in schizophrenia (SCZ)
is in perceptual organization (PO) – the processes by which individual elements of sensory information are collectively structured into larger units of perceived objects and their interrelations
(Palmer, 1999). Over 50 studies have demonstrated reduced PO in
SCZ (for reviews, see Uhlhaas and Silverstein (2005), Silverstein
and Keane (2011)). Some of these studies suggest that, among
psychiatric conditions, PO impairment is specific to SCZ, in that it
has not been observed in mixed groups of psychotic patients
without SCZ, in non-psychotic patients, or in patients who abuse
drugs that are not psychotomimetic (Silverstein and Keane, 2011)
[there is debate, however, over whether autism, another neurodevelopmental disorder, is characterized by reduced PO (Dakin
and Frith, 2005; Sun et al., 2012)].
Recently, however, perceptual impairments that may be aspects of, or secondary to, reduced PO have been observed in body
dysmorphic disorder (BDD), a condition characterized by preoccupation with perceived defects in visual appearance. For example, Feusner et al. demonstrated that BDD patients are impaired
at processing low spatial frequency information in faces, and
S.M. Silverstein et al. / Psychiatry Research 229 (2015) 426–433
427
demonstrate hypoactivity in occipital regions during processing of
low spatial frequency information from own face, other face, and
object stimuli (Feusner et al., 2007, 2010a, 2010b, 2010c, 2011).
Patients with BDD and individuals with a high degree of body
image concern also show a reduced face inversion effect (i.e., a
worsening of performance when making judgments about faces
that are upended compared to upright faces) (Feusner et al.,
2010b; Jefferies et al., 2012; Mundy and Sadusky, 2014). Because
the face inversion effect has traditionally been thought to reflect
the contrast between rapid configural processing of upright faces
versus slower serial processing of inverted faces (Tanaka and Farah, 1993; Tanaka and Sengco, 1997; Freire et al., 2000; Taubert
et al., 2011; Peters et al., 2013) (but see Rakover (2013), Civile et al.
(2014), Xu and Biederman (2014) for other accounts of the effect),
and because low spatial frequency information carries the majority of information about global form (Tanaka and Farah, 1993;
Costen et al., 1996; Deruelle and Fagot, 2005), these data suggest a
reduction in PO in BDD. Of note, patients with SCZ have shown
performance impairments on tasks that are similar to the ones
used to study face processing in BDD, including reduced face inversion effects (Schwartz et al., 2002; Chen et al., 2008; Soria
Bauser et al., 2012; Tsunoda et al., 2012) (but see Chambon et al.
(2006), Butler et al. (2008)), reduced processing of low spatial
frequency information in faces (Silverstein et al., 2010), and reduced encoding of the structural features of faces (Turetsky et al.,
2007; Tsunoda et al., 2012). To date, however, no studies directly
comparing BDD and SCZ on visual perception have been
conducted.
The purpose of this pilot study was, therefore, to directly
compare BDD and SCZ patients on two measures of PO that have
repeatedly shown sensitivity to impairments in SCZ: an Ebbinguaus illusion task and a contour integration (CI) task. In addition,
a group of obsessive–compulsive disorder (OCD) patients was included to control for obsessive–compulsive features, and to determine whether problems in organizational strategies that have
been observed in OCD (e.g., on verbal and visual memory tasks
(Deckersbach et al., 2000a, 2000b, 2000c; Savage et al., 2000)
could account for task performance in BDD. Psychiatrically healthy
controls were also included.
1.1. Ebbinghaus illusion
In a typical Ebbinghaus illusion demonstration, the perceived
size of a circle is altered when it is surrounded by other circles; it
appears larger than its actual size when surrounded by smaller
circles and smaller than its actual size when surrounded by larger
circles (see Fig. 1). The effect has been known for over 100 years
(Titchener, 1902), and has been the subject of numerous experiments, especially since the 1970s (e.g., Massaro and Anderson,
1971; Girgus et al., 1972; Weintraub and Schneck, 1986; Coren and
Enns, 1993; Rose and Bressan, 2002; Doherty et al., 2010;
Schwarzkopf and Rees, 2013). Patients with schizophrenia have
demonstrated reduced illusion effects, expressed as more accurate
size perception compared to controls when judging target circle
size in misleading context conditions (Uhlhaas et al., 2006; Silverstein et al., 2013; Tibber et al., 2013). This effect is most pronounced when patients have active psychotic symptoms (Silverstein et al., 2013).
1.2. Contour integration
CI is one of the most widely used measures of PO in the SCZ and
basic vision literatures (Field et al., 1993; Kovacs and Julesz, 1993;
Polat et al., 1997; Kovacs, 2000; Chandna et al., 2001). CI is typically measured as the ability to detect or make a judgment about a
closed contour made up of non-contiguous elements, embedded
Fig. 1. Sample stimuli from each of the 2 conditions (bottom 2 panels) of the Ebbinghaus illusion task. In each case, the target circle on the right is larger than the
one on the left. The top panel shows the actual circle sizes, for comparison.
within a display of randomly oriented elements (see Fig. 2). Previous studies have shown that people with SCZ are less able to
detect and make shape judgments about contours when compared
to healthy, psychotic, non-psychotic and non-psychotomimetic
substance abusing control groups (Uhlhaas and Silverstein, 2005;
Silverstein and Keane, 2011). CI impairment has also been observed in aging (Roudaia et al., 2011), dyslexia (Simmers and Bex,
2001), and amblyopia (Polat et al., 1997), and can be affected by
psychotomimetic drugs that affect occipital lobe functioning
(Uhlhaas et al., 2007; White et al., 2013). To our knowledge, only
one prior study has investigated CI in BDD (Rossell et al., 2014).
This recent study found normal performance; however, they used
an older, card-based version of the task with only 15 stimuli and a
lengthy exposure duration (30 s). In the present study, we used a
recently developed computerized version of the CI task with a
large number of trials and a relatively brief stimulus duration
(Silverstein et al., 2012).
428
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2.3. Perceptual organization Tasks
2.3.1. Apparatus
Stimuli at the Rutgers site (SCZ and CON groups) were presented on Samsung
2243BWX LCD monitors with viewable dimensions of 47.5 by 29.8 cm. The screen
resolution was 1680 1050 pixels, viewing distance was 24 in. (61.0 cm), and
therefore, the viewable screen subtended 43° 27° of visual angle. Monitor parameters were a gamma value of 2.2, color temperature (white point) of 6500 K, and
luminance of 120 cd/m2. Stimuli at the Massachusetts General Hospital site (BDD
and OCD groups) were presented on a Hewlett Packard Compaq nc8430 LCD laptop
monitor with a viewable dimension of 33.1 by 20.7 cm. The screen resolution was
1680 1050 pixels, viewing distance was 18 in. (45.7 cm), and the viewable screen
subtended 40° 26° of visual angle. Therefore, the stimuli were very similar between sites, but not quite identical—at MGH, one pixel subtended .0247 deg2 and at
Rutgers, .0266 deg2 (i.e., MGH stimuli were 93% as large as those at Rutgers). At
MGH, monitor parameters were a gamma value of 2.2, color temperature (white
point) of 6500 K, and luminance of 112.9 cd/m2.
Fig. 2. Sample stimuli from the contour integration test. Top left: 7–8° jitter,
leaving a still visible contour. Top right: 15–16° jitter, leaving a contour that most
people cannot detect. Bottom left: Catch trial with line drawn through contour, to
eliminate the need for grouping. Bottom right: Catch trial with no background,
eliminating effects of noise.
2. Methods
2.1. Subjects
Four groups participated: (1) outpatients with BDD (n¼20; 11 female);
(2) outpatients with OCD (n ¼20, 7 female); (3) inpatients with SCZ (n¼ 24; 11
female); and (4) controls (CON) without a psychiatric disorder (n¼ 20; 10 female).
BDD and OCD patients were recruited from specialized clinics at the Department of
Psychiatry at Massachusetts General Hospital (MGH). All BDD participants were
required to have a score of Z 20 on the BDD version of the Yale–Brown Obsessive–
Compulsive Disorder Scale (BDD-YBOCS) (Phillips et al., 1997). All OCD participants
were required to have a score of Z 16 on the Yale–Brown Obsessive–Compulsive
Disorder Scale (YBOCS) (Goodman et al., 1989a, 1989b). Thirteen BDD patients and
10 OCD patients were taking medication at the time of testing. Patients with
schizophrenia were recruited from the adult psychiatric inpatient unit at Rutgers
University Behavioral Health Care. All SCZ patients were hospitalized while tested,
and were tested within 1 week of admission. All were taking second-generation
antipsychotic medication at the time of testing. The CON group was recruited from
the local community. Data from 58% of the SCZ and 50% of the CON groups only was
included in a prior report (Silverstein et al., 2013). More details on exclusion criteria
and patient medications can be found in Supplemental information.
2.2. Clinical assessments
SCZ, BDD and OCD diagnoses were confirmed via the Structured Clinical Interview for DSM-IV diagnosis (SCID) (First et al., 2002b), in addition to collateral
information obtained from clinical staff and the electronic medical record. BDD and
OCD groups only also completed the Brown Assessment of Beliefs Scale (BABS)
(Eisen et al., 1998) and the Peters’ Delusional Inventory (PDI) (Peters et al., 1999) to
assess insight and delusionality, in addition to the Y-BOCS and BDD-YBOCS as noted
above. Symptoms were assessed for the SCZ group with the Positive and Negative
Syndrome Scale (PANSS) (Kay et al., 1987) which was scored using a 5 factor model
that included orthogonal factors for positive, negative, cognitive, depression, and
excitement symptoms (Lindenmayer et al., 1994a, 1994b, 1995a, 1995b). We also
derived a separate disorganization factor (Cuesta and Peralta, 1995), and focused
specifically on item P2, conceptual disorganization, given prior observed relationships between reduced PO, including CI, and reduced thought organization in SCZ
(Uhlhaas and Silverstein, 2005; Silverstein and Keane, 2011). Lack of psychiatric
diagnosis for the CON group was confirmed with the SCID, non-patient version
(First et al., 2002a).
2.3.2. Ebbinghaus illusion task
On each trial, the task was to press a key to indicate whether the target on the
left or the right half of the screen was larger (see Fig. 1). All circles were black and
presented on a white background. The stimulus appeared on the screen until the
subject responded or after two seconds (whichever happened first). If a response
was not recorded within 2 s of stimulus onset, the trial was counted as a guess (.5
correct) so as not to penalize subjects who preferred to time-out rather than guess
on a trial. Trials were separated by 200 ms. The targets were centered on either side
of the screen and appeared with surrounding circles (see below). The two target
circles always differed in actual size, and this difference varied in magnitude across
trials. As noted, the size of the objects at MGH were 93% the size of the objects at
Rutgers. At the Rutgers site, the center circle on one side was always 2.67° of visual
angle in diameter, while the center circle on the other side was always .05°, .16°,
.27°, .37°, or .48° larger or smaller. The side on which the larger circle appeared was
randomized across trials. This size comparison was presented in 2 conditions. (1) In
the misleading condition, the target circles were always surrounded by 8 larger
circles arranged in a square configuration (i.e., 3 above, one on each side, and
3 below, see Fig. 1). Each of the five size differences was shown sixteen times, with
the larger central circle always surrounded by larger circles (for Rutgers 3.33° in
diameter) and the smaller central circle always surrounded by smaller circles (for
Rutgers 1.33° in diameter). In this condition, size contrast impairs discrimination by
biasing the observer to perceive the larger target as smaller and the smaller target
as larger (Doherty et al., 2008). (2) In the helpful context condition, the two target
circles (for Rutgers 2.61° and 2.72° of visual angle) were presented eight times each,
again surrounded by 8 circles around the edges of an imaginary square, with the
smaller center circle surrounded by larger circles (for Rutgers 3.33° in diameter)
and the larger central circle surrounded by smaller circles (for Rutgers 1.33° in
diameter). In this condition, size contrast increases accuracy. Note that in this
condition, if subjects choose the array with larger surrounds then they will be
wrong on every trial. As in prior studies, only 16 trials were presented in the helpful
condition, and they were all at the hardest difficulty level (for Rutgers.05° size
difference between center circles) (Phillips et al., 2004; Doherty et al., 2008, 2010).
The 96 trials in the context conditions (80 in the misleading and 16 in the helpful
conditions) were presented in a different random order for each subject. The primary performance index for this study was that of context sensitivity, defined as
the difference between scores in the 16-trial helpful condition and scores in the 16trials from the misleading condition with the same target-surround size difference
as in the helpful condition (Silverstein et al., 2013).
2.3.3. Contour integration test
Participants were shown static Gabor elements forming an oblong shaped
contour embedded in a display of randomly oriented Gabor elements (see Fig. 2).
On each trial, participants responded whether the narrow end of the oblong contour was pointing left or right. Perceptual organization was manipulated by adding
orientation jitter to the Gabor elements forming the contours, across 6 levels: 7 0°,
7–8°, 9–10°, 11–12°, 13–14°, and 15–16°. For all stimuli, there were 207 noise Gabor,
and 15 contour-defining Gabor elements. The ratio of the density of adjacent
background elements to the density of adjacent contour elements was .9:1.0. At this
level, adjacent background elements are closer together than adjacent contour
elements, and thus CI requires integration of activity at the spatial filters corresponding to the Gabor elements; perception of the contour by density cues is not
possible at D o1.0. All Gabor elements were identical except for their position and
orientation. At Rutgers, the average distance between adjacent elements was 1.0°.
The width and wavelength of each element was .2°. At MGH, the average distance
between adjacent elements was .93° and the width and wavelength of each element was .186°.
Each stimulus was presented for 2 s followed by a 1 s inter stimulus interval
during which responses were no longer recorded. Forty-eight stimulus trials per
jitter condition were presented in blocks of 12 trials. Two types of catch stimuli (i.e.,
no errors expected) using 0° jitter were administered during each block to assess
momentary attention lapses. One had curved lines drawn through the contours to
S.M. Silverstein et al. / Psychiatry Research 229 (2015) 426–433
429
highlight contour salience, and the other contained contour elements without
background elements to eliminate distractor noise effects. Blocks were presented in
increasing order of difficulty (starting with 0° and ending at 15–16°), and each
6-block sequence was repeated 4 times for a total of 288 experimental and 48 catch
trials. Total score across all jitter conditions (excluding catch trials) was used as the
performance index as this score has higher test-retest reliability compared to
psychometric function threshold values (Strauss et al., 2014). As in prior studies
(Silverstein et al., 2012; Feigenson et al., 2014), a timed-out response was scored as
.5 correct, to not give any advantage to subjects who preferred to guess rather than
time-out on a trial.
2.4. Ethics
All procedures contributing to this work comply with the ethical standards of
Rutgers and MGH IRBs. All subjects provided written informed consent.
3. Results
3.1. Demographic data
Table 1 summarizes demographic and psychometric data. Data
on comorbid conditions can be found in Supplemental results.
The groups did not differ in sex composition: Pearson's
Χ2(3) ¼1.75, p ¼.63. There was a significant between-group difference in age: F(3, 83) ¼3.17, p o.05. Post-hoc Tukey tests indicated that the SCZ group (mean ¼42.25, SD ¼11.16) was significantly older than the BDD (31.55 , 12.36) group, but not the
CON (38.1 and 11.86) or OCD (36.10 and 11.29) groups. There were
no other significant pairwise differences.
3.2. Ebbinghaus illusion
The 4 groups were compared across the helpful and misleading
indices with a 4(group) 2(condition) ANOVA with repeated
measures on the condition factor. As predicted, there was a significant effect of condition, with accuracy being superior in the
helpful context compared to the misleading context condition: F
(1.80)¼ 41.16, p o.001, partial eta squared¼.34. The main effect of
group was not significant: F(3.80) ¼1.96, p ¼.13, partial eta
squared¼.068. However, the group x condition interaction was
significant [F(3.80) ¼ 3.39, po .05, partial eta squared¼.11; see
Fig. 3]. This interaction was explored by comparing groups on the
context sensitivity index. The main effect of group on this index
Fig. 3. Ebbinghaus illusion: Context sensitivity values, by group. Error bars represent 1 SD. Dotted line represents post-hoc pairwise group difference at the .01
level of statistical significance. Dashed line represents a pairwise difference at
p o.05.
was significant [F(3.80) ¼4.23, p o.001, partial eta squared¼ .14].
Pairwise comparisons (Tukey) revealed that the expected group
difference between SCZ and CON (SCZoCON) was observed,
p¼ .01, replicating past studies of reduced context sensitivity in
SCZ. The SCZ group also demonstrated reduced context sensitivity
compared to the BDD and OCD groups at close to the.05 level (p
values were .049 and .051, respectively). Pairwise comparisons
between the BDD, OCD, and CON groups were all associated with p
values greater than .95.
3.3. Contour integration test
There were no effects of group for either type of catch trial [for
line type, F(3.79) ¼ 1.83, p ¼ .15; for no background type, F(3.79) ¼
2.24, p ¼.09] indicating that all groups were paying adequate attention to the task. On the non-catch trials, the SCZ group had the
lowest proportion correct (see Fig. 4). Including all jitter conditions
in a mixed model ANOVA (group jitter) revealed the expected
main effect of jitter [F(5.395) ¼194.61, po .001], a trend towards a
Table 1
Means (SDs) for study variables, by group.
Ageb
Ebbinghaus – misleading contextb
Ebbinghaus – helpful contextb
Ebbinghaus – context sensitivityb
Contour integration – main trialsn
Contour integration – catch trial: line
Contour integration – catch trial: no noise
Y-BOCSb
BDD Y-BOCSb
BABSb
PDI
PANSS – positive
PANSS – negative
PANSS – cognitive
PANSS – excitement
PANSS – depression
PANSS – disorganization
PANS – conceptual disorganization
*
p ¼ .01.
po .05.
b
po .01.
b
po .001.
b
BDD (n¼20)
OCD (n¼20)
SCZ (n¼24)
CON (n¼ 20)
31.55(12.36)
37.39(26.38)
86.14(27.15)
11.15(8.45)
65.38(13.89)
92.71(22.78)
93.54(22.72)
3.25(6.92)
26.65(4.88)
11.15(5.21)
6.50(4.88)
*******
*******
*******
*******
*******
*******
*******
36.10(11.29)
47.21(23.83)
87.17(29.30)
11.10(8.50)
65.89(10.97)
98.33(3.42)
97.71(3.44)
22.75(4.85)
3.90(7.73)
2.70(5.88)
9.2(11.43)
*******
*******
*******
*******
*******
*******
*******
42.25(11.16)
60.77(26.90)
67.40(39.06)
3.88(11.83)
62.80(9.83)
89.93(17.15)
89.93(15.68)
*******
*******
*******
*******
12.13(3.53)
16.79(3.75)
11.38(3.05)
9.54(3.19)
14.04(4.87)
5.96(2.01)
2.13(1.15)
38.10(11.86)
47.13(19.67)
91.48(19.62)
12.60(6.14)
71.35(11.00)
97.50(4.36)
98.33(2.49)
*******
*******
*******
*******
*******
*******
*******
*******
*******
*******
*******
430
S.M. Silverstein et al. / Psychiatry Research 229 (2015) 426–433
Fig. 4. Contour integration test: Proportion accuracy, by group. Error bars represent
1 SD. Solid lines represent group differences at the.001 level of statistical significance in post-hoc pair-wise comparisons. Dashed line represents a pairwise
difference at po .05.
main effect of group [F(3.79) ¼2.50, p ¼.066], and a non-significant
group x jitter interaction [F(15.395) ¼.44, p¼ .97], the latter replicating past studies comparing controls and schizophrenia patients. When total proportion correct (summed across all conditions) was used as the dependent variable, however, a significant
effect of group was observed: [F(3.79) ¼ 7.67, po .001]. Post-hoc
tests (Tukey) indicated that the SCZ group achieved significantly
lower scores than the BDD (p¼ .017), OCD (p ¼.001), and CON
(p ¼.001) groups. The BDD and OCD groups did not differ from
each other or from the CON group. Further exploratory post-hoc
analyses indicated that the groups did not differ in performance at
jitter levels 0°, 7°, or 9° (the 3 easiest conditions) or 15° (the most
difficult condition). However, at 11° jitter, the SCZ group performed more poorly than the CON group (p¼ .023), and at 13°
jitter, the SCZ group performed more poorly than the OCD
(p ¼.021) and CON (p ¼.033) groups. Similar results to those reported above were observed when age (which can be inversely
correlated with contour integration (Del Viva and Agostini, 2007;
Roudaia et al., 2011)) was used as a covariate, and when catch trial
scores were used as covariates.
3.4. Relationships between symptoms and task performance for the
BDD, OCD, and SCZ groups
There were no relationships between task scores and symptoms for any group, with one exception (for the SCZ group) that
would not survive correction for multiple comparisons. See Supplemental information for details.
4. Discussion
The primary finding from this study was that BDD patients do
not perform as schizophrenia patients do on two-well validated
measures of PO. Rather, their performance was statistically indistinguishable from that of OCD and psychiatrically healthy control
groups. Our results are consistent with earlier studies that found
normal performance among BDD patients on tasks that have been
previously associated with abnormalities in schizophrenia, (Reese
et al., 2011a, 2011b), including a recently published study demonstrating normal CI (Rossell et al., 2014), despite the prevalence
of delusional thinking regarding personal appearance in many
BDD patients seen in clinical settings (Phillips et al., 2006). One
potential implication of these findings is that PO impairment may
be somewhat specific to schizophrenia, and perhaps other clearly
neurodevelopmental conditions such as autism (Sun et al., 2012)
among psychiatric disorders. This has been the conclusion in
several earlier studies that used mixed groups of patients with
psychotic disorders other than schizophrenia (Silverstein et al.,
1996, 2000), patients with non-psychotic psychiatric disorders
(Uhlhaas et al., 2006), or people with non-psychotomimetic substance abuse disorders (Place and Gilmore, 1980; Uhlhaas et al.,
2006) as control groups, and found normal performance therein.
Several limitations of the study must be noted. One is that only
two tasks were included. Since scores on different tests involving
PO are not always highly correlated (Joseph et al., 2013), and since
PO occurs at multiple stages of visual information processing
(Palmer et al., 2003), it is possible that it involves multiple components. This raises the possibility that SCZ and BDD could both be
impaired, but on different sub-processes, and that the tests we
included are not sensitive to BDD-specific impairment. Related to
this, it is possible that inclusion of tests on which BDD patients are
known to perform poorly (e.g., face inversion (Feusner et al.,
2010b)) would have revealed domains of greater similarity between the SCZ and BDD groups. This of course raises the issue of
the nature of the perceptual impairment in BDD, which will be
addressed below. Second, 13 of the 20 BDD participants, half of the
OCD, and all of the SCZ participants were medicated. While antipsychotic medication does not appear to affect PO (Silverstein and
Keane, 2011), little is known about the perceptual effects of serotonin reuptake inhibitors, and it is possible that they may have
resulted in normalization of underlying perceptual disturbances. A
third limitation is that the symptom assessment measures given to
the patients differed across diagnostic groups. While the measures
used were typical and appropriate for clinical and research assessment of each group, a more thorough evaluation of group similarities and differences in PO might have been possible if data
on each of the scales were available for all patients regardless of
diagnosis. A fourth limitation is that the display devices used to
present the tasks differed across the two sites. We consider it
unlikely that the pattern of results we observed is related to this,
given the similarity in the tasks’ basic effects across multiple
studies (cited above) using these identical tasks within the context
of variation in display devices, and therefore in stimulus size and
brightness. For the CI task, this includes similar results from studies where controls and patients were each tested at different,
non-standardized sites (Kozma-Weibe et al., 2006), where controls
and patients were both tested at multiple sites (Silverstein et al.,
2012), and where controls and patients were tested at the same
single site (Silverstein et al., 2000, 2009). In addition, the luminance measurements of the monitors, and stimulus sizes, at Rutgers and MGH were very similar (e.g., MGH stimuli were 93% as
large as Rutgers’). And, importantly, scale invariance (i.e., similarity
in results across variations in stimulus size) has been previously
demonstrated for the CI task (Hess and Dakin, 1997; Keane et al.,
2014). A fifth limitation is that the BDD and SCZ groups differed in
age, with the latter group being older. This is potentially problematic because perceptual organization, in the form of contour
integration, has been shown to gradually decline with age in later
adulthood (Del Viva and Agostini, 2007; Roudaia et al., 2008).
However, the overall pattern of findings in the study, especially the
expected differences between the SCZ and CON groups, cannot be
explained by age since these two groups did not differ in age.
A final, and perhaps most important, limitation is that the SCZ
group was an inpatient group while the BDD and OCD groups were
outpatients. This was a deliberate aspect of the study design, because both tasks included in this study have demonstrated
S.M. Silverstein et al. / Psychiatry Research 229 (2015) 426–433
relationships with disorganized and psychotic symptoms in past
studies, whereas performance is often much closer to normal after
symptom remission (Uhlhaas et al., 2006; Silverstein et al., 2013).
This is thought to reflect improvements in underlying mechanisms
(computational and neurobiological) that are common to these
symptoms and to aspects of abnormal perception, rather than
simply the result of reduced interference from symptoms on task
performance after symptoms remit (Phillips and Silverstein, 2003).
So, rather than simply reflecting greater overall disability in the
SCZ group, our findings can be taken as further evidence that
schizophrenia-related processes are connected with abnormal PO.
We consider it unlikely that the group differences simply reflect
inpatient vs. outpatient status, since: (1) among SCZ patients in
this study, we observed moderate effects (but at the trend level of
evidence) for relationships between poorer context sensitivity (on
the Ebbinghaus illusion task) and conceptual disorganization – a
symptom that often leads to hospitalization (see Supplemental
information), and these effects have been observed at statistically
significant levels in several prior studies (Uhlhaas and Silverstein,
2005; Silverstein and Keane, 2011); this symptom is not characteristic of either BDD or OCD, however; (2) CI performance has
been shown to be stable from inpatient admission to discharge in
SCZ patients, (Feigenson et al., 2014), and so similar results to
those we observed can be expected in most outpatients with
schizophrenia on the CI task; and (3) other groups of inpatients,
including psychotic patients without schizophrenia, people with
non-psychotomimetic substance abuse disorders, and brain injured patients with behavior disorders, all perform normally on
either or both of the tests used in this study (Silverstein et al.,
2000; Uhlhaas et al., 2005, 2006). However, it cannot be ruled out
that BDD and/or OCD patients who require hospitalization for their
OCD spectrum conditions might perform more abnormally on the
two perception tasks compared to the patients included in this
study, and so this requires further investigation.
A major question raised by the data involves the nature of the
perceptual impairment in BDD. While earlier studies (reviewed in
the Introduction) suggested an impairment in global form processing that might indicate reduced PO in BDD, the problem may
lie elsewhere. For example, recent work on the face inversion effect suggests that it may not be due to an inability to process
global features of inverted faces. Rather, it may be due to the more
rapid (top-down) application of face-specific schemata during interpretation of sensory information in the upright faces condition
(Rakover, 2013). This raises the possibility that high-level perceptual and/or emotional factors in BDD, distinct from PO, may
interfere with this process. Alternatively, since in both studies that
found reduced face inversion effects in BDD (Feusner et al., 2010b;
Jefferies et al., 2012), the differences were due to better performance than controls with inverted faces, yet similar performance
with upright faces, it is possible that individuals with BDD may
have a tendency to preferentially allocate attention to processing
details, particularly when allowed longer viewing durations, even
when PO is normal.
It is also possible that reduced occipital activation in laboratory
perception tasks among people with BDD reflects excessive modulation of feedforward perceptual activity, perhaps driven by
emotional factors. This possibility has not yet been studied, although the ability of prefrontal areas to modulate occipital activity
is now generally accepted (Cavada et al., 2000; Rainer and Miller,
2000; Petrides et al., 2002; van Turennout et al., 2003; Hasson
et al., 2004; Bar et al., 2006; Deshpande et al., 2010; Chaumon
et al., 2014; Volberg et al., 2013; Volberg and Greenlee, 2014).
Moreover, the amygdala provides input to the frontal cortex that
can affect perception (Sabatinelli et al., 2014), and emotion affects
the likelihood that arousing information will be processed (Phelps
et al., 2006), as well as how quickly it is processed (Ohman et al.,
431
2001). The amygdala is also connected to both the ventral and
dorsal visual streams; through these pathways, top-down signals
may be carried to the visual cortex to enhance visual processing
for emotionally salient stimuli (Furl et al., 2013), which may shift
balances in global and local processing. In individuals with BDD,
Bohon et al. (2012) found associations between brain activity in
amygdala and in the ventral visual stream, as well as an association between anxiety and ventral visual stream activity, suggesting
that arousal may increase processing of details in this population.
In addition, expectations regarding what one will see can affect
how much attention is allocated to processing a stimulus (Bressler
et al., 2008). These data suggest that heightened emotional activity, especially regarding one's own appearance, excessively
modulates the feedforward sweep of visual information, so that
perception is excessively dominated by emotion-syntonic schemata. However, hypoactivity in visual association areas in BDD has
been observed not only for emotionally-salient stimuli (own and
others’ faces) but also for stimuli that are not normally emotionally
arousing (e.g., pictures of houses) (Feusner et al., 2011).
Finally, several studies of BDD have demonstrated reduced
processing of low spatial frequency (LSF) information. While this
typically carries information about global form, reduced LSF processing does not necessarily lead to reduced PO. Another function
of LSF processing is to direct attention to relevant aspects in the
visual field (Bar et al., 2006). It is therefore possible that reduced
LSF processing in BDD serves as a setting condition for allocation
of visual attention to be driven more by internal factors than by
global form, even if global form can be processed normally under
many conditions. All of these potential scenarios suggest the
possibility of a perception and emotion-mediated attentional bias
in BDD that is different from what characterizes schizophrenia, but
that can, in some cases, lead to similar clinical phenomena.
Conflicts of interest
None.
Acknowledgments
We would like to thank Amanda Calkins, Lillian Reuman, Yushi
Wang, and Danielle Paterno for their help with recruitment and
testing. This research was supported in part by fellowship support
awarded to Corinna Elliott from the Fonds de Recherche du Quebéc-Santé (FRQS), by NIMH Grant R01MH093439 to the first author, by NIH IRACDA Postdoctoral Training Grant 1K12GM09385405 to M. W. Roché, and by funding from The Neil and Anna Rasmussen Foundation to the last author.
Appendix A. Supplementary material
Supplementary data associated with this article can be found in
the online version at doi:10.1016/j.psychres.2015.05.107
References
Bar, M., Kassam, K.S., Ghuman, A.S., Boshyan, J., Schmid, A.M., Dale, A.M., Hamalainen, M.S., Marinkovic, K., Schacter, D.L., Rosen, B.R., Halgren, E., 2006. Topdown facilitation of visual recognition. Proc. Natl. Acad. Sci. 103, 449–454.
Bellivier, F., Geoffroy, P.A., Scott, J., Schurhoff, F., Leboyer, M., Etain, B., 2013. Biomarkers of bipolar disorder: specific or shared with schizophrenia? Front.
Biosci. 5, 845–863.
Bohon, C., Hembacher, E., Moller, H., Moody, T.D., Feusner, J.D., 2012. Nonlinear
relationships between anxiety and visual processing of own and others’ faces in
432
S.M. Silverstein et al. / Psychiatry Research 229 (2015) 426–433
body dysmorphic disorder. Psychiatry Res. 204, 132–139.
Bressler, S.L., Tang, W., Sylvester, C.M., Shulman, G.L., Corbetta, M., 2008. Top-down
control of human visual cortex by frontal and parietal cortex in anticipatory
visual spatial attention. J. Neurosci. 28, 10056–10061.
Butler, P.D., Tambini, A., Yovel, G., Jalbrzikowski, M., Ziwich, R., Silipo, G., Kanwisher,
N., Javitt, D.C., 2008. What's in a face? Effects of stimulus duration and inversion on face processing in schizophrenia. Schizophr. Res. 103, 283–292.
Cavada, C., Company, T., Tejedor, J., Cruz-Rizzolo, R.J., Reinoso-Suarez, F., 2000. The
anatomical connections of the macaque monkey orbitofrontal cortex. A review.
Cereb. Cortex 10, 220–242.
Chambon, V., Baudouin, J.Y., Franck, N., 2006. The role of configural information in
facial emotion recognition in schizophrenia. Neuropsychologia 44, 2437–2444.
Chandna, A., Pennefather, P.M., Kovacs, I., Norcia, A.M., 2001. Contour integration
deficits in anisometropic amblyopia. Investig. Ophthalmol. Vis. Sci. 42,
875–878.
Chaumon, M., Kveraga, K., Barrett, L.F., Bar, M., 2014. Visual predictions in the orbitofrontal cortex rely on associative content. Cereb. Cortex 24, 2899–2907.
Chen, Y., Norton, D., Ongur, D., Heckers, S., 2008. Inefficient face detection in
schizophrenia. Schizophr. Bull. 34, 367–374.
Civile, C., McLaren, R.P., McLaren, I.P., 2014. The face inversion effect – parts and
wholes: individual features and their configuration. Q. J. Exp. Psychol. 67,
728–746.
Coren, S., Enns, J.T., 1993. Size contrast as a function of conceptual similarity between test and inducers. Percept. Psychophys. 54, 579–588.
Costen, N.P., Parker, D.M., Craw, I., 1996. Effects of high-pass and low-pass spatial
filtering on face identification. Percept. Psychophys. 58, 602–612.
Cuesta, M.J., Peralta, V., 1995. Psychopathological dimensions in schizophrenia.
Schizophr. Bull. 21, 473–482.
Cuthbert, B.N., Insel, T.R., 2010. Toward new approaches to psychotic disorders: the
NIMH Research Domain Criteria Project. Schizophr. Bull. 36, 1061–1062.
Dakin, S., Frith, U., 2005. Vagaries of visual perception in autism. Neuron 48,
497–507.
Deckersbach, T., Otto, M.W., Savage, C.R., Baer, L., Jenike, M.A., 2000a. The relationship between semantic organization and memory in obsessive–compulsive disorder. Psychother. Psychosom. 69, 101–107.
Deckersbach, T., Savage, C.R., Henin, A., Mataix-Cols, D., Otto, M.W., Wilhelm, S.,
Rauch, S.L., Baer, L., Jenike, M.A., 2000b. Reliability and validity of a scoring
system for measuring organizational approach in the complex figure test. J.
Clin. Exp. Neuropsychol. 22, 640–648.
Deckersbach, T., Savage, C.R., Phillips, K.A., Wilhelm, S., Buhlmann, U., Rauch, S.L.,
Baer, L., Jenike, M.A., 2000c. Characteristics of memory dysfunction in body
dysmorphic disorder. J. Int. Neuropsychol. Soc. 6, 673–681.
Del Viva, M.M., Agostini, R., 2007. Visual spatial integration in the elderly. Investig.
Ophthalmol. Vis. Sci. 48, 2940–2946.
Deruelle, C., Fagot, J., 2005. Categorizing facial identities, emotions, and genders:
attention to high- and low-spatial frequencies by children and adults. J. Exp.
Child Psychology 90, 172–184.
Deshpande, G., Hu, X., Lacey, S., Stilla, R., Sathian, K., 2010. Object familiarity
modulates effective connectivity during haptic shape perception. NeuroImage
49, 1991–2000.
Doherty, J.L., Owen, M.J., 2014. Genomic insights into the overlap between psychiatric disorders: implications for research and clinical practice. Genome Med.
6, 29.
Doherty, M.J., Campbell, N.M., Tsuji, H., Phillips, W.A., 2010. The Ebbinghaus illusion
deceives adults but not children. Dev. Sci. 13, 714–721.
Doherty, M.J., Tsuji, H., Phillips, W.A., 2008. The context sensitivity of visual size
perception varies across cultures. Perception 37, 1426–1433.
Eisen, J.L., Phillips, K.A., Baer, L., Beer, D.A., Atala, K.D., Rasmussen, S.A., 1998. The
brown assessment of beliefs scale: reliability and validity. Am. J. Psychiatry 155,
102–108.
Feigenson, K.A., Keane, B.P., Roche, M.W., Silverstein, S.M., 2014. Contour integration
impairment in schizophrenia and first episode psychosis: state or trait? Schizophr. Res. 159, 515–520.
Feusner, J.D., Bystritsky, A., Hellemann, G., Bookheimer, S., 2010a. Impaired identity
recognition of faces with emotional expressions in body dysmorphic disorder.
Psychiatry Res. 179, 318–323.
Feusner, J.D., Hembacher, E., Moller, H., Moody, T.D., 2011. Abnormalities of object
visual processing in body dysmorphic disorder. Psychol. Med. 41, 2385–2397.
Feusner, J.D., Moller, H., Altstein, L., Sugar, C., Bookheimer, S., Yoon, J., Hembacher,
E., 2010b. Inverted face processing in body dysmorphic disorder. J. Psychiatric
Res. 44, 1088–1094.
Feusner, J.D., Moody, T., Hembacher, E., Townsend, J., McKinley, M., Moller, H.,
Bookheimer, S., 2010c. Abnormalities of visual processing and frontostriatal
systems in body dysmorphic disorder. Arch. Gen. Psychiatry 67, 197–205.
Feusner, J.D., Townsend, J., Bystritsky, A., Bookheimer, S., 2007. Visual information
processing of faces in body dysmorphic disorder. Arch. Gen. Psychiatry 64,
1417–1425.
Field, D.J., Hayes, A., Hess, R.F., 1993. Contour integration by the human visual
system: evidence for a local “association field”. Vis. Res. 33, 173–193.
First, M., Spitzer, R., Gibbon, M., Williams, J.B.W., 2002a. Structured clinical interview for DSM-IV-TR Axis I Disorders, Research Version, Non-Patient Edition
(SCID-I/NP). Biometics Research, New York State Psychiatric Institute, New
York, NY.
First, M., Spitzer, R., Gibbon, M., Williams, J.B.W., 2002b. Structured clinical interview for DSM-IV-TR Axis I Disorders, Research Version, Patient Edition (SCID-I/
P). Biometrics Research, New York State Psychiatric Institute, New York, NY.
Freire, A., Lee, K., Symons, L.A., 2000. The face-inversion effect as a deficit in the
encoding of configural information: direct evidence. Perception 29, 159–170.
Furl, N., Henson, R.N., Friston, K.J., Calder, A.J., 2013. Top-down control of visual
responses to fear by the amygdala. J. Neurosci. 33, 17435–17443.
Girgus, J.S., Coren, S., Agdern, M., 1972. The interrelationship between the Ebbinghaus and Delboeuf illusions. J. Exp. Psychol. 95, 453–455.
Goodman, W.K., Price, L.H., Rasmussen, S.A., Mazure, C., Delgado, P., Heninger, G.R.,
Charney, D.S., 1989a. The Yale–Brown Obsessive Compulsive Scale. II. Validity.
Arch. Gen. Psychiatry 46, 1012–1016.
Goodman, W.K., Price, L.H., Rasmussen, S.A., Mazure, C., Fleischmann, R.L., Hill, C.L.,
Heninger, G.R., Charney, D.S., 1989b. The Yale–Brown Obsessive Compulsive
Scale. I. Development, use, and reliability. Arch. Gen. Psychiatry 46, 1006–1011.
Guilmatre, A., Dubourg, C., Mosca, A.L., Legallic, S., Goldenberg, A., Drouin-Garraud,
V., Layet, V., Rosier, A., Briault, S., Bonnet-Brilhault, F., Laumonnier, F., Odent, S.,
Le Vacon, G., Joly-Helas, G., David, V., Bendavid, C., Pinoit, J.M., Henry, C., Impallomeni, C., Germano, E., Tortorella, G., Di Rosa, G., Barthelemy, C., Andres, C.,
Faivre, L., Frebourg, T., Saugier Veber, P., Campion, D., 2009. Recurrent rearrangements in synaptic and neurodevelopmental genes and shared biologic
pathways in schizophrenia, autism, and mental retardation. Arch. Gen. Psychiatry 66, 947–956.
Hasson, U., Nir, Y., Levy, I., Fuhrmann, G., Malach, R., 2004. Intersubject synchronization of cortical activity during natural vision. Science 303, 1634–1640.
Hess, R.F., Dakin, S.C., 1997. Absence of contour linking in peripheral vision. Nature
390, 602–604.
Insel, T., Cuthbert, B., Garvey, M., Heinssen, R., Pine, D.S., Quinn, K., Sanislow, C.,
Wang, P., 2010. Research domain criteria (RDoC): toward a new classification
framework for research on mental disorders. Am. J. Psychiatry 167, 748–751.
Jefferies, K., Laws, K.R., Fineberg, N.A., 2012. Superior face recognition in body
dysmorphic disorder. J. Obsessive–Compuls. Relat. Disord. 1, 175–179.
Joseph, J., Bae, G., Silverstein, S.M., 2013. Sex, symptom, and premorbid social
functioning associated with perceptual organization and dysfunction in schizophrenia. Front. Psychol. 4, 547. http://dx.doi.org/10.3389/fpsyg.2013.00547.
Kay, S.R., Fiszbein, A., Opler, L.A., 1987. The positive and negative syndrome scale
(PANSS) for schizophrenia. Schizophr. Bull. 13, 261–276.
Keane, B.P., Erlikhman, G., Kastner, S., Paterno, D., Silverstein, S.M., 2014. Multiple
forms of contour grouping deficits in schizophrenia: what is the role of spatial
frequency? Neuropsychologia 65, 221–233.
Kovacs, I., 2000. Human development of perceptual organization. Vis. Res. 40,
1301–1310.
Kovacs, I., Julesz, B., 1993. A closed curve is much more than an incomplete one:
effect of closure in figure-ground segmentation. Proc. Natl. Acad. Sci. 90; , pp.
7495–7497.
Kozma-Weibe, P., Silverstein, S.M., Feher, A., Kovacs, I., Uhlhaas, P., Wilkniss, S.,
2006. Development of a World-Wide-Web based contour integration test: reliability and validity. Comput. Hum. Behav. 22, 971–980.
Lindenmayer, J.P., Bernstein-Hyman, R., Grochowski, S., 1994a. Five-factor model of
schizophrenia. Initial validation. J. Nerv. Ment. Dis. 182, 631–638.
Lindenmayer, J.P., Bernstein-Hyman, R., Grochowski, S., 1994b. A new five factor
model of schizophrenia. Psychiatr. Q. 65, 299–322.
Lindenmayer, J.P., Bernstein-Hyman, R., Grochowski, S., Bark, N., 1995a. Psychopathology of Schizophrenia: initial validation of a 5-factor model. Psychopathology 28, 22–31.
Lindenmayer, J.P., Grochowski, S., Hyman, R.B., 1995b. Five factor model of schizophrenia: replication across samples. Schizophr. Res. 14, 229–234.
Massaro, D.W., Anderson, N.H., 1971. Judgmental model of the Ebbinghaus illusion.
J. Exp. Psychol. 89, 147–151.
Monzani, B., Rijsdijk, F., Harris, J., Mataix-Cols, D., 2014. The structure of genetic and
environmental risk factors for dimensional representations of DSM-5 obsessive–compulsive spectrum disorders. JAMA Psychiatry 71, 182–189.
Mundy, E.M., Sadusky, A., 2014. Abnormalities in visual processing amongst students with body image concerns. Adv. Cognit. Psychol. 10, 39–48.
Ohman, A., Flykt, A., Esteves, F., 2001. Emotion drives attention: detecting the snake
in the grass. J. Exp. Psychol.: Gen. 130, 466–478.
Palmer, S.E., 1999. Vision Science: Photons to Phenomenology. MIT Press, Cambridge, MA.
Palmer, S.E., Brooks, J.L., Nelson, R., 2003. When does grouping happen? Acta
Psychol. 114, 311–330.
Peters, E.R., Joseph, S.A., Garety, P.A., 1999. Measurement of delusional ideation in
the normal population: introducing the PDI (Peters et al. Delusions Inventory).
Schizophr. Bull. 25, 553–576.
Peters, J.C., Vlamings, P., Kemner, C., 2013. Neural processing of high and low spatial
frequency information in faces changes across development: qualitative
changes in face processing during adolescence. Eur. J. Neurosci. 37, 1448–1457.
Petrides, M., Alivisatos, B., Frey, S., 2002. Differential activation of the human orbital, mid-ventrolateral, and mid-dorsolateral prefrontal cortex during the
processing of visual stimuli. Proc. Natl. Acad. of Sci. 99; , pp. 5649–5654.
Phelps, E.A., Ling, S., Carrasco, M., 2006. Emotion facilitates perception and potentiates the perceptual benefits of attention. Psychol. Sci. 17, 292–299.
Phillips, K.A., Hollander, E., Rasmussen, S.A., Aronowitz, B.R., DeCaria, C., Goodman,
W.K., 1997. A severity rating scale for body dysmorphic disorder: development,
reliability, and validity of a modified version of the Yale–Brown Obsessive
Compulsive Scale. Psychopharmacol. Bull. 33, 17–22.
Phillips, K.A., Menard, W., Pagano, M.E., Fay, C., Stout, R.L., 2006. Delusional versus
nondelusional body dysmorphic disorder: clinical features and course of illness.
J. Psychiatr. Res. 40, 95–104.
Phillips, W.A., Chapman, K.L., Berry, P.D., 2004. Size perception is less context-
S.M. Silverstein et al. / Psychiatry Research 229 (2015) 426–433
sensitive in males. Perception 33, 79–86.
Phillips, W.A., Silverstein, S.M., 2003. Convergence of biological and psychological
perspectives on cognitive coordination in schizophrenia. Behav. Brain Sci. 26,
65–82, discussion 82–137.
Place, E.J., Gilmore, G.C., 1980. Perceptual organization in schizophrenia. J. Abnorm.
Psychol. 89, 409–418.
Polat, U., Sagi, D., Norcia, A.M., 1997. Abnormal long-range spatial interactions in
amblyopia. Vis. Res. 37, 737–744.
Rainer, G., Miller, E.K., 2000. Effects of visual experience on the representation of
objects in the prefrontal cortex. Neuron 27, 179–189.
Rakover, S.S., 2013. Explaining the face-inversion effect: the face-scheme incompatibility (FSI) model. Psychon. Bull. Rev. 20, 665–692.
Reese, H.E., McNally, R.J., Wilhelm, S., 2011a. Probabilistic reasoning in patients with
body dysmorphic disorder. J. Behav. Ther. Exp. Psychiatry 42, 270–276.
Reese, H.E., McNally, R.J., Wilhelm, S., 2011b. Reality monitoring in patients with
body dysmorphic disorder. Behav. Ther. 42, 387–398.
Rose, D., Bressan, P., 2002. Going round in circles: shape effects in the Ebbinghaus
illusion. Spat. Vis. 15, 191–203.
Rossell, S.L., Labuschagne, I., Dunai, J., Kyrios, M., Castle, D.J., 2014. Using theories of
delusion formation to explain abnormal beliefs in Body Dysmorphic Disorder
(BDD). Psychiatry Res. 215, 599–605.
Roudaia, E., Bennett, P.J., Sekuler, A.B., 2008. The effect of aging on contour integration. Vis. Res. 48, 2767–2774.
Roudaia, E., Farber, L.E., Bennett, P.J., Sekuler, A.B., 2011. The effects of aging on
contour discrimination in clutter. Vis. Res. 51, 1022–1032.
Sabatinelli, D., Frank, D.W., Wanger, T.J., Dhamala, M., Adhikari, B.M., Li, X., 2014.
The timing and directional connectivity of human frontoparietal and ventral
visual attention networks in emotional scene perception. Neuroscience 277,
229–238.
Savage, C.R., Deckersbach, T., Wilhelm, S., Rauch, S.L., Baer, L., Reid, T., Jenike, M.A.,
2000. Strategic processing and episodic memory impairment in obsessive
compulsive disorder. Neuropsychology 14, 141–151.
Schwartz, B.L., Marvel, C.L., Drapalski, A., Rosse, R.B., Deutsch, S.I., 2002. Configural
processing in face recognition in schizophrenia. Cognit. Neuropsychiatry 7,
15–39.
Schwarzkopf, D.S., Rees, G., 2013. Subjective size perception depends on central
visual cortical magnification in human V1. PLoS One 8, e60550.
Silverstein, S.M., All, S.D., Kasi, R., Berten, S., Essex, B., Lathrop, K.L., Little, D.M.,
2010. Increased fusiform area activation in schizophrenia during processing of
spatial frequency-degraded faces, as revealed by fMRI. Psychol. Med. 40,
1159–1169.
Silverstein, S.M., Berten, S., Essex, B., Kovacs, I., Susmaras, T., Little, D.M., 2009. An
fMRI examination of visual integration in schizophrenia. J. Integr. Neurosci. 8,
175–202.
Silverstein, S.M., Keane, B.P., 2011. Perceptual organization impairment in schizophrenia and associated brain mechanisms: review of research from 2005 to
2010. Schizophr. Bull. 37, 690–699.
Silverstein, S.M., Keane, B.P., Barch, D.M., Carter, C.S., Gold, J.M., Kovacs, I., MacDonald 3rd, A., Ragland, J.D., Strauss, M.E., 2012. Optimization and validation of a
visual integration test for schizophrenia research. Schizophr. Bull. 38, 125–134.
Silverstein, S.M., Keane, B.P., Wang, Y., Mikkilineni, D., Paterno, D., Papathomas, T.V.,
Feigenson, K., 2013. Effects of short-term inpatient treatment on sensitivity to a
size contrast illusion in first-episode psychosis and multiple-episode schizophrenia. Front. Psychol. 4, 466.
Silverstein, S.M., Knight, R.A., Schwarzkopf, S.B., West, L.L., Osborn, L.M., Kamin, D.,
1996. Stimulus configuration and context effects in perceptual organization in
schizophrenia. J. Abnorm. Psychol. 105, 410–420.
Silverstein, S.M., Kovacs, I., Corry, R., Valone, C., 2000. Perceptual organization, the
disorganization syndrome, and context processing in chronic schizophrenia.
Schizophr. Res. 43, 11–20.
433
Simmers, A.J., Bex, P.J., 2001. Deficit of visual contour integration in dyslexia. Investig. Ophthalmol. Vis. Sci. 42, 2737–2742.
Soria Bauser, D., Thoma, P., Aizenberg, V., Brune, M., Juckel, G., Daum, I., 2012. Face
and body perception in schizophrenia: a configural processing deficit? Psychiatry Res. 195, 9–17.
Strauss, M.E., McLouth, C.J., Barch, D.M., Carter, C.S., Gold, J.M., Luck, S.J., MacDonald
3rd, A.W., Ragland, J.D., Ranganath, C., Keane, B.P., Silverstein, S.M., 2014.
Temporal stability and moderating effects of age and sex on CNTRaCS task
performance. Schizophr. Bull. 40, 835–844.
Sun, L., Grutzner, C., Bolte, S., Wibral, M., Tozman, T., Schlitt, S., Poustka, F., Singer,
W., Freitag, C.M., Uhlhaas, P.J., 2012. Impaired gamma-band activity during
perceptual organization in adults with autism spectrum disorders: evidence for
dysfunctional network activity in frontal-posterior cortices. J. Neurosci. 32,
9563–9573.
Tanaka, J.W., Farah, M.J., 1993. Parts and wholes in face recognition. Q. J. Exp.
Psychol. A 46, 225–245.
Tanaka, J.W., Sengco, J.A., 1997. Features and their configuration in face recognition.
Mem. Cognit. 25, 583–592.
Taubert, J., Apthorp, D., Aagten-Murphy, D., Alais, D., 2011. The role of holistic
processing in face perception: evidence from the face inversion effect. Vis. Res.
51, 1273–1278.
Tibber, M.S., Anderson, E.J., Bobin, T., Antonova, E., Seabright, A., Wright, B., Carlin,
P., Shergill, S.S., Dakin, S.C., 2013. Visual surround suppression in schizophrenia.
Front Psychol. 4 (88). http://dx.doi.org/10.3389/fpsyg.2013.00088.
Titchener, E.B., 1902. Experimental Psychology. The MacMillan Company, New
York, NY.
Tsunoda, T., Kanba, S., Ueno, T., Hirano, Y., Hirano, S., Maekawa, T., Onitsuka, T.,
2012. Altered face inversion effect and association between face N170 reduction
and social dysfunction in patients with schizophrenia. Clin. Neurophysiol. 123,
1762–1768.
Turetsky, B.I., Kohler, C.G., Indersmitten, T., Bhati, M.T., Charbonnier, D., Gur, R.C.,
2007. Facial emotion recognition in schizophrenia: when and why does it go
awry? Schizophr. Res. 94, 253–263.
Uhlhaas, P.J., Millard, I., Muetzelfeldt, L., Curran, H.V., Morgan, C.J., 2007. Perceptual
organization in ketamine users: preliminary evidence of deficits on night of
drug use but not 3 days later. J. Psychopharmacol. 21, 347–352.
Uhlhaas, P.J., Phillips, W.A., Mitchell, G., Silverstein, S.M., 2006. Perceptual grouping
in disorganized schizophrenia. Psychiatry Research 145, 105–117.
Uhlhaas, P.J., Phillips, W.A., Silverstein, S.M., 2005. The course and clinical correlates
of dysfunctions in visual perceptual organization in schizophrenia during the
remission of psychotic symptoms. Schizophrenia Res. 75, 183–192.
Uhlhaas, P.J., Silverstein, S.M., 2005. Perceptual organization in schizophrenia
spectrum disorders: empirical research and theoretical implications. Psychol.
Bull. 131, 618–632.
van Turennout, M., Bielamowicz, L., Martin, A., 2003. Modulation of neural activity
during object naming: effects of time and practice. Cereb. Cortex 13, 381–391.
Volberg, G., Greenlee, M.W., 2014. Brain networks supporting perceptual grouping
and contour selection. Front. Psychol. 5, 264.
Volberg, G., Wutz, A., Greenlee, M.W., 2013. Top-down control in contour grouping.
PLoS One 8, e54085.
Weintraub, D.J., Schneck, M.K., 1986. Fragments of Delboeuf and Ebbinghaus illusions: contour/context explorations of misjudged circle size. Atten. Percept.
Psychophys. 40, 147–158.
White, C., Brown, J., Edwards, M., 2013. Altered visual perception in long-term
ecstasy (MDMA) users. Psychopharmacology 229, 155–165.
Xu, X., Biederman, I., 2014. Neural correlates of face detection. Cereb. Cortex 24,
1555–1564.