A new cue to figure–ground coding: top–bottom
Vision Research 44 (2004) 2779–2791
www.elsevier.com/locate/visres
A new cue to figure–ground coding: top–bottom polarity
Johan Hulleman *, Glyn W. Humphreys
School of Psychology, University of Birmingham, Birmingham B15 2TT, UK
Received 8 March 2004; received in revised form 7 June 2004
Abstract
We present evidence for a new figure–ground cue: top–bottom polarity. In an explicit reporting task, participants were more
likely to interpret stimuli with a wide base and a narrow top as a figure. A similar advantage for wide-based stimuli also occurred
in a visual short-term memory task, where the stimuli had ambiguous figure–ground relations. Further support comes from a figural
search task.
Figural search is a discrimination task in which participants are set to search for a symmetric target in a display with ambiguous
figure–ground organization. We show that figural search was easier when stimuli with a top–bottom polarity were placed in an
orientation where they had a wide base and a narrow top, relative to when this orientation was inverted. This polarity effect was
present when participants were set to use color to parse figure from ground, and it was magnified when the participants did not
have any foreknowledge of the color of the symmetric target.
Taken together the results suggest that top–bottom polarity influences figure–ground assignment, with wide base stimuli being
preferred as a figure. In addition, the figural search task can serve as a useful procedure to examine figure–ground assignment.
2004 Elsevier Ltd. All rights reserved.
Keywords: Perceptual organization; Figure–ground segregation
1. Introduction
In 1917, Rubin published his observations about the
alternative perceptual organizations of his famous figure-vase stimulus. On the one hand, the stimulus can
be interpreted as two faces looking at each other in front
of a rectangle; on the other it can also be seen as a vase
in front of the same rectangle, with the color of the rectangle now changed. In the many years that have since
passed, research has indicated that figure–ground organization is influenced by a variety of cues including: Symmetry, convexity, surroundedness, area, familiarity and
spatial frequency (see Palmer, 1999 for a discussion).
Recently, Vecera, Vogel, and Woodman (2002) have
added Ôlower regionÕ to this list. They demonstrated a
*
Corresponding author. Tel.: +44 121 4143679.
E-mail address: [email protected] (J. Hulleman).
0042-6989/$ - see front matter 2004 Elsevier Ltd. All rights reserved.
doi:10.1016/j.visres.2004.06.012
bias in figure–ground organization such that the bottom
half of a whole visual display tended to be taken as the
figure, and the top half as the ground.
One of the problems in studying figure–ground
organization is in choosing a task that reflects figure–
ground coding, but that is not affected by other factors.
In the vast majority of studies, observers have simply
been asked to record what they saw as a figure (an explicit reporting task). However, this introspective process
can be affected by many factors. For instance, with
ambiguous stimuli there can be individual biases in
maintaining or in wishing to switch from one organization to another, which can have quite dramatic effects on
performance (e.g. Strüber & Stadler, 1999). An alternative procedure, less dependent on introspective biases,
has been to use visual short-term memory tasks
(VSTM-task, introduced by Driver & Baylis, 1996).
For example, observers may be presented with an
ambiguous figure–ground stimulus for a certain period
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(the study display), followed by a test display containing
one of the regions from the ambiguous study display.
The idea is that the figural region will have a stronger
memory trace, so that the reaction times (RTs) will be
faster when the subsequent region matches the perceived
figure rather than the perceived ground in the study
display (see Vecera et al., 2002, for an example). This
method has become something of a gold standard in
figure–ground research. Even this method, though,
might not be without its problems. For instance, it is
possible that effects in short-term memory tasks are
caused by properties of the second, test display, rather
than the original study display containing the ambiguous figure–ground stimulus.
So, it seems that, in order to establish that a certain
cue influences figure–ground assignment, the prudent
approach would be to use all the methods that are available, rather than to rely on a single approach. For instance, Vecera et al. (2002) used both explicit reporting
tasks and the VSTM-method to establish that lower region is a figure–ground cue. In the present study we use
both of the above procedures, plus also a new method
(‘‘figural search’’) to establish another new cue for figure–ground assignment: top–bottom polarity. We use
the evidence to argue both for the role of this new cue,
and for the utility of figural search as a means to examine figure–ground coding.
We employed abstract shapes, depicted within a band
pattern stimulus as used by Metzger (1936). Examples
are shown in Fig. 1. The abstract shapes were constructed so that they had two long horizontal elements
either at the base, and two short horizontal elements at
the top (wide base) or two short horizontal elements at
the base and the two long horizontal elements at the
top (wide top). This resulted in a strong top–bottom
polarity (see the Method).
2. Experiment 1: direct report
In Experiment 1 we used an explicit report task to
provide direct evidence on any effect of top–bottom
polarity on figure–ground coding. We presented a group
of participants with ambiguous figure–ground displays.
There were four displays (see Fig. 1), with the wide base
regions being black for two displays and white for two
displays (and vice versa for the wide top regions). For
each display, participants had to decide whether the
white or the black regions were seen as the figure.
2.1. Method
The study was run in a classroom testing situation.
There were 55 participants (38 female, 17 male), all
undergraduates in Psychology at the University of Birmingham (aged between 19 and 22). The four displays
Fig. 1. The four stimuli used in Experiment 1.
were shown one at a time, projected onto a large screen
at the front of the classroom. The order of the displays
was randomly determined. All the regions of the band
patterns were asymmetric. Participants were not allowed
to confer, and they made a written response to each display. In an initial pilot experiment, 22 observers were
asked to view a pair of stimuli from the set used here,
but with just a single element from the band patterns
used to represent the Ôwide topÕ and Ôwide baseÕ stimulus
in each pair. A forced choice decision was then required
as to whether the Ôwide topÕ or the Ôwide baseÕ stimulus
was upright. A set of 8 pairs was shown. Twenty participants chose all 8 stimuli with a Ôwide baseÕ as upright.
One participant chose 1 stimulus as upright from the
Ôwide topÕ items. One other participant chose 3 stimuli
with a wide top as upright. Thus overwhelmingly
observers chose the Ôwide baseÕ items as upright.
2.2. Results
The percentages of the participants who reported the
wide base shapes as figure were 89%, 76%, 84% and 71%
J. Hulleman, G.W. Humphreys / Vision Research 44 (2004) 2779–2791
respectively, for the four displays. Tested binomially, all
four percentages differ significantly from 50% (all
pÕs < 0.001).
2.3. Discussion
There was a substantial and reliable bias in the explicit report of which part of an ambiguous display was
perceived as ÔfigureÕ. Participants were biased to interpret the wide base regions as figural. This occurred irrespective of whether these regions were white or black.
Note that all the regions were asymmetric, and that
the participants were not engaged in a symmetry detection task. Therefore, the results cannot be attributed to
effects of top–bottom polarity on symmetry perception,
nor on symmetry biasing the figure–ground assignment.
As pointed out in the Introduction, explicit reporting
methods need to be supplemented by more implicit
methods, because the deliberate nature of explicit
reporting tasks leaves open the possibility of extraneous
factors. In the remainder of the experiments, we therefore used implicited methods, to provide converging evidence that top–bottom polarity acts as a figure–ground
cue. In Experiment 2, we used the VSTM-task and in
Experiments 3 and 4 we used a new implicit task, the figural search task.
3. Experiment 2: matching shapes in VSTM
In the VSTM task, participants are presented with a
display with an ambiguous figure–ground relationship
between black and white regions. This is followed by a
pair of test shapes (unambiguous figures against the
overall ground; see Fig. 2). The task is to decide which
Fig. 2. Sequence of displays in Experiment 2. After the presentation of
a fixation dot, the study stimulus was presented for 200 ms. After a 500
ms blank interval, the test display appeared. The test displays remained
visible until response, or until 15 s had elapsed.
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of the test shapes had a bounding contour that matched
the border between the black and white regions. Performance is better if the contour of the matching test
shape corresponds to the boundary of the figural region
in the initial display (Driver & Baylis, 1996). Here we
would expect a benefit when the contour matches the
boundary of the wide base stimulus, rather than the
wide top stimulus.
3.1. Method
3.1.1. Participants
Twenty-two participants (20 female, 2 male) were recruited either in return for course credit or for a small
payment. All had corrected or corrected-to-normal vision, and they were unaware of the purpose of this
experiment.
3.1.2. Apparatus
A Pentium III PC controlled the experiment and presented the stimuli on a 17 in. VGA-monitor, in 800 ·
600 graphics mode.
3.1.3. Stimuli
The participants looked unrestrained at the stimuli
from standard viewing distance (around 50 cm). The stimulus used in the study display contained two juxtaposed
shapes, one black and one white (3.7 · 3.7), presented
on a gray background. The test display contained two
dark gray shapes (2.1 · 3.7). Examples are shown in
Fig. 6. The study stimulus appeared at the center of the
screen. The vertical size of an individual shape was 3.7.
A half of a shape consisted of 10 arms, each arm having
a thickness of 0.37. The maximum width of an arm was
1.1. The minimum width was 0.2. The shapes were always asymmetric. The shapes were rotationally symmetric. As a result, a shape and its 180 rotated version fit
each other like a jig-saw when juxtaposed. This yields a
natural control for non-specific effects on the figure–
ground assignment, because the shape preferred as a figure and the shape preferred as a ground are identical. In
this experiment we used 15 different shapes. Each shape
was used 16 times: The wide-base shape could be on the
left or on the right, the wide-base shape could be black
or could be white, and the test display could contain a figural match for the wide-base shape or the wide-top shape,
with the correct answer either on the left or the right.
3.1.4. Procedure
The participants were tested individually in a session
that lasted approximately 20 min. After receiving the
instruction for the task, participants performed a practice block of 16 trials. When they felt at ease with the
task, they would start the experimental blocks, otherwise they would get another practice block of 16 trials.
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A trial consisted of a fixation circle presented in the
center of the screen for 500 ms. After the fixation circle
disappeared, the stimulus was presented for 200 ms.
After a blank display that lasted 500 ms, the test display
appeared, and remained on the screen until the participant responded or 30,000 ms had passed. After the response, there was an inter-trial interval of 1000 ms,
before a new trial would start (see Fig. 2). The task of
the participants was to decide which of the two shapes
presented in the test display had a bounding contour
that corresponded to the border between the black and
the white shape seen in the study display. If it was the
shape on the left, they had to press the ÔnÕ on the keyboard as quickly as possible. For the shape on the right
the Ô/Õ key was used.
3.1.5. Design
There were two within-subject factors: study position
(wide base item left, wide base item right), and figural
match (left item, right item). The factors were fully
crossed (see Fig. 3 for examples of the four possible com-
binations). If top–bottom polarity biases figure–ground
assignment, we would expect an interaction between
these two factors: if during the study display the wide
base item appears on the left, the figural match of the left
item should be faster, but the figural match of the right
item should be faster if the wide base item appears on
the right during the study display. In total, there were
240 trials. The experiment was subdivided into blocks
of 64. Between every block there was a self-paced break
for the participant. If a participant made an error, the error trial was retaken somewhere in the sequence of trials.
Each error resulted in an extra trial.
3.2. Results
The results are shown in Fig. 4. The data of one participant had to be discarded, because of an excessive
error rate (proportion correct: 0.46). The data of the
remaining 21 participants were entered into the analysis.
Responses greater or less than 2.5 SDs from the cell
mean (study position · figural match) for each partici-
Fig. 3. Examples of the stimuli used in Experiment 2. (A) Stimulus with the wide base stimulus on the left and the wide top stimulus on the right: (i)
test display with a figural match for the right item and (ii) test display with a figural match for the left item. (B) Stimulus with the wide base stimulus
on the right and the wide top stimulus on the left: (iii) test display with a figural match for the right item and (iv) test display with a figural match for
the left item.
J. Hulleman, G.W. Humphreys / Vision Research 44 (2004) 2779–2791
Reaction time [msec]
1000
Wide Base Item Left
Wide Base Item Right
950
900
850
800
Left Item
Right Item
Figural Match
0.2
Proportion Error
Wide Base Item Left
Wide Base Item Right
0.15
0.1
0.05
0
Left Item
Right Item
Figural Match
Fig. 4. Results of Experiment 2. Top panel: reaction times. Bottom
panel: error proportions. White: wide base item on the left in the study
display. Black: wide base item on the right in the study display. The
error bars indicate standard errors.
pant were rejected. This resulted in rejection of 2.8% of
the data. The error analysis was performed on all of the
remaining trials, whereas the reaction time analysis only
used the correct trials.
Critically, a two-way repeated measures ANOVA
(study position · figural match) on the RT data yielded
a significant interaction between study position and figural match, F(1,20) = 5.042, p < 0.037. Neither of the
main effects was significant (both pÕs > 0.49).
A similar ANOVA on the error-data did not yield
any significant effects. All p-values were 0.66 or above.
3.3. Discussion
The results of Experiment 2 support those obtained
in Experiment 1. The interaction between study position
and figural match indicates that there was an RT advantage for figural matches of the wide base region relative
to matches contingent on the wide top region. This
advantage is consistent with top–bottom polarity affecting figural assignment in the ambiguous displays.
Note that this result cannot be explained by effects of
top–bottom polarity on symmetry detection, because all
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the shapes here were asymmetric. Also, all RTs are well
within the range of times that have previously been accepted to be associated with figure–ground assignment
(e.g. Driver & Baylis, 1996, Vecera et al., 2002).
In Experiments 3 and 4 we used a new implicit method: the figural search task. It combines elements of both
the implicit (VSTM) and explicit report methods used in
prior studies. The task provides an on-line measure
(rather than a memory-based measure) of figure–ground
assignment, 1 but one where (as with the memory tasks)
observers are not explicitly required to report what they
see as a figure. We presented observers with displays
with ambiguous figure–ground relations, and asked
them to find a particular target shape (in our case, a vertically symmetric item). We will call this task figural
search, because it combines elements from figure–
ground research with visual search. If a given cue leads
to either an initial or dominant figure–ground organization, then the target shape revealed by this cue should be
easier to find than a target shape not revealed by this
cue. This then provides an indication that a particular
cue influences figure–ground assignment. Our expectation, that it will take longer to detect a symmetrical
shape when it belongs to the ground, is based on results
reported by Baylis and Driver (2001). They showed that
is more difficult to detect symmetry when the symmetrical edges belong to two different shapes (as is the case
when the target shape is seen as belonging to the
ground), than when the symmetrical edges belong to a
single shape (as is the case when the target shape is seen
as belonging to the figure).
4. Experiment 3: figural search for a known target color
In Experiment 3, participants were set to search for a
symmetrical target amongst asymmetrical distractors.
The target was also coded by color (either black or
white, against a gray background). Under these circumstances, participants should parse figural from ground
regions using color. The stimuli (abstract shapes) could
either have a wide base, or a wide top. We ask whether
the top–bottom polarity of the stimuli affected performance, even when figure–ground organization should be
based on color. We note that, although the task was
symmetry detection, there was only one symmetrical
shape in a display. Hence, figure–ground should not
be overwhelmingly determined by symmetry-effects of
color and top–bottom polarity may thus still emerge
(as indeed we observed).
1
With on-line, we mean that the participants make their response
while the ambiguous figure–ground stimulus is still available for
inspection.
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4.1. Method
4.1.1. Participants
Sixteen participants (13 female, 3 male) were recruited either in return for course credit or for a small
payment. All had corrected or corrected-to-normal vision, and they were unaware of the purpose of this
experiment.
4.1.2. Apparatus
A Pentium III PC controlled the experiment and presented the stimuli on a 17 in. VGA-monitor, in
800 · 600 graphics mode.
4.2. Stimuli
The participants looked unrestrained at the stimuli from a standard viewing distance (around 50 cm).
The stimuli were black and white band patterns
(3.7 · 12.4), presented on a gray background. Examples are shown in Fig. 5. The band patterns appeared
at the center of the screen. Each band pattern contained
eight complete objects and two half objects. Half of
them were black, the other half were white. The vertical
size of an individual shape was 3.7. A half of a shape
consisted of 16 arms, each arm having a thickness of
0.2. The maximum width of an arm was 1.1. The minimum width was 0.2. The arms of a half were paired:
the arm at the top end with the arm at the bottom
end, the second arm from the top with the second arm
from the bottom, etc. The lengths of a pair of arms
had to sum up to 1.4. For the wide base stimuli, the
halves were constructed in such a way that the two arms
at the bottom end of the shape always (nearly) had the
maximum width. Consequently, the two arms at the
top end always (nearly) had the minimum width. For
the wide top stimuli, this was inverted. The lengths of
the other arms were randomly chosen to be between
the minimum width and the maximum width. Complete
objects were created by combining two halves. In the
case of an asymmetric object, the halves were constructed independently, for symmetric objects the same
half was used twice.
An individual band pattern was used four times:
Once with the wide base items colored black and the
wide top items colored white, once with this color
assignment inverted, and both these versions were also
presented upside down.
4.2.1. Procedure
The participants were tested individually in a session
that lasted approximately 40 min. After receiving the
instruction for the task, participants performed a practice block of 16 trials. When they felt at ease with the
task, they would start the experimental blocks, otherwise they were given another practice block of 16 trials.
A trial consisted of a fixation cross presented in the
center of the screen for 1000 ms. After the fixation cross
disappeared, the band pattern was presented until the
participant responded or 15,000 ms had passed. After
the response, there was an inter-trial interval of 1000
ms, before a new trial would start. The task of the participants was to look for a vertically symmetric object of
a specified color on the screen. If it was present, they had
to push the ÔZÕ or ÔMÕ key on the keyboard as quickly as
possible. If it was absent, they had to push the other key
(ÔMÕ or ÔZÕ). The keys assigned to present and absent responses were counterbalanced over participants.
4.2.2. Design
There were three within-subject factors: top–bottom
polarity (wide base, wide top), target presence (symmetric target present, symmetric target absent), and the color of the stimuli (black, white). All the factors were fully
crossed. In total, there were 640 trials. The target colors
were blocked, resulting in two groups of 320 trials. The
groups contained blocks of 80 trials. Between every
block there was a self paced break for the participant.
If a participant made an error, the error trial was retaken somewhere in the sequence of trials. Each error resulted in an extra trial. After the first target color was
tested, there was a new training sequence of sixteen trials, to give the participants the opportunity to acquaint
themselves with the new target color.
4.3. Results
Fig. 5. Examples of displays with ambiguous figure–ground relations
used in Experiments 3 and 4. Top half: target color black; and Bottom
half: target color white.
The results are shown in Fig. 6. Responses greater or
less than 2.0 SDs from the cell mean (top–bottom polarity · target presence · color) for each participant were
rejected. This resulted in rejection of 4.2% of the data.
The error analysis was performed on all of the remain-
J. Hulleman, G.W. Humphreys / Vision Research 44 (2004) 2779–2791
4.4. Discussion
Reaction Time [msec]
2500
Wide Base
2250
Wide Top
2000
1750
1500
1250
1000
Absent
(A)
Present
Symmetric Target
0.125
Wide Base
Proportion Error
0.100
Wide Top
0.075
0.050
0.025
0.000
Absent
(B)
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Present
Symmetric Target
Fig. 6. Results of Experiment 3: (A) reaction times and (B) error rates.
Black: wide base stimuli. White: wide top stimuli. Left: symmetric
target absent. Right: symmetric target present. The error bars indicate
standard errors.
ing trials, whereas the reaction time analysis only used
the correct trials.
A three way repeated measures ANOVA (top–bottom polarity · target presence · color) on the reaction
time data yielded significant main effects for target presence, F(1,15) = 55.9, p < 0.001 and top–bottom polarity,
F(1,15) = 15.8, p < 0.002. Present responses were faster
than absent, and responses to targets with a wide base
were faster than responses to targets with a wide top.
There were no other significant main effects nor were
there any significant interactions.
A similar ANOVA on the error-data resulted in significant main effects for target presence, F(1,15) = 17.9,
p < 0.002, and top–bottom polarity, F(1,15) = 17.8,
p < 0.002. Moreover, there was a significant interaction
between target presence and top–bottom polarity,
F(1,15) = 8.6, p < 0.011. There were more errors on present trials than on absent trials, and fewer for targets
with a wide base than for targets with a wide top. This
advantage for wide-base targets was most pronounced
on target present trials. For all the other main effects
and interactions, the p-values were larger than 0.2.
We consider the figural search task as a form of visual
search in which participants have to select a symmetrical
target from asymmetric distractors. Olivers and Van der
Helm (1998) have shown that visual search for a symmetrical target is inefficient, and the long reaction times
and high error rates for the present figural search task
are consistent with this. More interesting is that figural
search was affected by the top–bottom polarity of the
target shape, even though the color of the target was
pre-specified so that participants should have been set
to organize figure–ground relations on the basis of color. For the reaction time measure, the effect was quite
substantial and equally large on present and absent trials (an overall effect of around 100 ms). In addition to
this, there was a high error rate, with targets with a wide
top being particularly hard to detect (a miss rate of
nearly 10%). However, even though there are more errors on present trials than on absent trials, there are always more errors in the wide top condition than in the
wide base condition. So the polarity effect we observe
is not caused by speed-accuracy trade-off.
The long reaction times and high miss rate for widetop targets may come about because top–bottom polarity is a powerful factor influencing figure–ground
organization. To detect a target with a wide top, participants must create and maintain a representation in
which the wide top stimuli are coded as ÔfigureÕ, and
the wide base stimuli as ÔgroundÕ. The data suggest that
it is difficult to do this.
Symmetry has repeatedly been reported as a determiner of figure and ground (e.g. Driver & Baylis,
1996; Palmer, 1999). However, the 100 ms difference between the wide base and the wide top conditions cannot
be attributed to the presence or absence of a symmetric
target. Both the wide base and the wide top conditions
contained the same number of symmetrical targets. If
symmetry biased the assignment of figure and ground,
we would have expected to find no difference between
the wide base and the wide top conditions.
However, other accounts are still possible. For example, it may simply be that visual search through items
with a wide top is more difficult than search through
items with a wide base, and this is unrelated to figure–
ground segmentation. Several investigators have demonstrated that visual search is influenced by the perceived
orientations of stimuli, with asymmetries favoring oblique over vertical stimuli (Treisman & Souther, 1985)
and stimuli in unusual over ÔstandardÕ orientations
(Wolfe, 2001). Given the similarities between visual
search and our figural search tasks, it may be that, in
Experiment 3, we witness an asymmetry, favoring items
with a wide base over items with a wide top (Note that
this would actually constitute a case of a standard orientation being favored). The results of Experiments 1 and
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2, where we found an effect of top–bottom polarity on
figure–ground assignment with tasks that are unrelated
to visual search, suggest it is unlikely that a search
assymmetry is the only explanation, but it might be a
contributing factor. To test this, in Experiment 4, we included a new manipulation. In one condition we used
stimuli with ambiguous figure–ground relations (as in
Experiment 3), but this time we allowed the targets to
be either black or white on a trial. Thus color was no
longer a reliable cue to figure–ground organization. If
part of the benefit to wide base stimuli in Experiment
3 was because they bias figure–ground assignment, then
even stronger effects of top–bottom polarity could occur
here, since the moderating effect of another factor (the
color cue) was eliminated.
In the second condition, participants were presented
with displays in which individual search elements did
not have ambiguous figure–ground relations (for the
most part being completely surrounded by the overall
gray background). This condition was included because
pilot work indicated that the figural search task without
color instruction was quite difficult. We therefore felt it
was necessary to include an ÔeasyÕ condition, in order to
keep the participants motivated. Moreover, if figural
search is indeed comparable to visual search, this unambiguous condition should yield reaction times similar to
those in Experiment 3.
So, both the ambiguous and the unambiguous configuration conditions of Experiment 4 are to be compared
with the results of Experiment 3, rather than with each
other.
5. Experiment 4: figural search for an unknown target
color
5.1. Method
5.1.1. Participants
Sixteen participants (13 female, 3 male) were recruited, either in return for course credit or for a small
payment. All had corrected or corrected-to-normal
vision, and they were unaware of the purpose of the
experiment.
5.1.2. Apparatus
The apparatus was the same as used in Experiment 3.
5.1.3. Stimuli
The ambiguous stimuli used in this experiment were
the same as those used in Experiment 3. The unambiguous stimuli were closely related to the ambiguous forms
(see Fig. 7 for examples of displays with unambiguous
figure–ground relationships). The individual shapes
were identical to the shapes in the ambiguous displays.
The background rectangle was again included, and
had the same dimensions as the ambiguous stimuli
(3.7 · 12.4). However, for the unambiguous displays
the individual shapes were vertically displaced to enable
them to be unambiguously coded as ÔfiguresÕ (being
small closed shapes against a much larger background).
The screen was subdivided into five horizontal bands
(2.3 wide), and each of the objects was randomly positioned in one of the bands. The maximum vertical overlap between two neighboring objects was 1.4. The
maximum height of an unambiguous display was therefore 14.4, the minimum height 10. There was no horizontal overlap, because the objects had horizontal
positions similar to those in the ambiguous displays.
For each of the wide base displays the configuration
(dispersion) of the objects was chosen randomly, and
the same configuration was then used for the wide top
displays. Again two color versions of the stimuli were
used, and both these color versions were also inverted.
5.1.4. Procedure
The participants were tested individually in a session
that lasted approximately 40 min. They were first given
the instructions for their task, and then they performed
a practice block of 16 trials. When the participants felt
at ease with the task, they would start the experimental
blocks, otherwise they would get another practice block
of 16 trials.
A trial consisted of a fixation cross presented in the
center of the screen for 1000 ms. After the fixation cross
disappeared, the stimulus display was presented until the
participant responded or 30,000 ms had passed. After
the response, there was an inter-trial interval of 1000
ms, before a new trial would start. The task was to look
for a vertically symmetric object. It could be either black
or white, and it was each color equally often. If the target was present participants had to push the present key
on the keyboard as quickly as possible. If it was absent,
they had to push the absent key. Responses were made
using the ÔZÕ and ÔMÕ keys, with the key used for the response counter-balanced over participants. Ambiguous
and unambiguous displays were intermixed.
5.1.5. Design
There were four within-subject factors: configuration
(ambiguous, unambiguous), top–bottom polarity (wide
base, wide top), target presence (symmetric target present, symmetric target absent), and the color of the stimuli (black, white). All the factors were fully crossed. In
total, there were 512 trials. There were eight blocks, containing 64 trials each. Between every block there was a
self-paced break for the participant. Pilot work indicated high error rates, so we did not retake any of the
error trials, to prevent demotivation of the participants.
J. Hulleman, G.W. Humphreys / Vision Research 44 (2004) 2779–2791
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Fig. 7. Examples of displays with unambiguous figure–ground relations used in Experiment 4: (A) unambiguous black targets and (B) unambiguous
white targets.
5.2. Results
The results are shown in Fig. 8. Responses greater or
less than 2.0 SDs from the cell mean (configuration · top–bottom polarity · target presence · color)
for each participant were rejected. This resulted in rejection of 4.3% of the data. The error analysis was performed on all of the remaining trials, whereas the
reaction time analysis only used the correct trials.
A four-way repeated measures ANOVA on the reaction time data yielded a host of significant main
effects and interactions. All four main effects were significant: configuration F(1,15) = 31.0, p < 0.001, target
presence F(1,15) = 63.0, p < 0.001, top–bottom polarity
F(1,15) = 11.5, p < 0.004 and color F(1,15) = 14.5,
p < 0.002. Moreover, there were significant interactions
between configuration and target presence F(1,15) =
15.8, p < 0.002, configuration and top–bottom polarity F(1,15) = 7.7, p < 0.015, configuration and color
F(1,15) = 4.8, p < 0.045, and a three way interaction between configuration, target presence and color
F(1,15) = 8.0, p < 0.015. To analyze the data further,
we separated the results for ambiguous and unambiguous configurations.
For the unambiguous configuration, there was only a
significant effect of target presence F(1,15) = 82.4,
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J. Hulleman, G.W. Humphreys / Vision Research 44 (2004) 2779–2791
effects of target presence, F(1,15) = 23.2, p < 0.001 and
top–bottom polarity, F(1,15) = 9.8, p < 0.005 and an
interaction between the two, F(1,15) = 9.5, p < 0.01.
The error rate was greater on present than absent trials,
and for targets with a wide top relative to a wide base.
There was no effect of color and no reliable interactions
involving this factor after Bonferroni-correction.
5.3. Discussion
Fig. 8. Results of Experiment 4 as a function of color, target presence
and the ambiguity of figure–ground relations. Top panel: reaction
times. Bottom panel: error rates. The error bars indicate standard
errors.
p < 0.001. None of the other main effects or interactions
approached significance (pÕs > 0.15).
For the ambiguous configuration, there were significant main effects of target presence F(1,15) = 82.4,
p < 0.001,
top–bottom
polarity
F(1,15) = 12.4,
p < 0.004 and color F(1,15) = 10.4, p < 0.006. No interactions were reliable with a Bonferroni corrected a of
0.025. Reaction times were faster on present than absent
trials, for white relative to black shapes, and for targets
with a wide base relative to targets with a wide top.
A four-way repeated measures ANOVA on the error
data resulted in significant main effects of configuration,
F(1,15) = 23.7, p < 0.001, target presence, F(1,15) =
26.0, p < 0.001, top–bottom polarity, F(1,15) = 8.8,
p < 0.01. Moreover, there were significant interactions
between configuration and target presence, F(1,15) =
16.7, p < 0.001, between configuration and top–bottom
polarity, F(1,15) = 8.9, p < 0.01, and target presence
and top–bottom polarity F(1,15) = 7.7, p < 0.015. There
was also a three-way interaction between configuration,
target presence and top–bottom polarity, F(1,15) = 11.2,
p < 0.005. Splitting the analysis along the configuration
dimension, for unambiguous stimuli there was only a
significant effect of target presence, F(1,15) = 7.5, p <
0.02. For ambiguous stimuli there were significant main
There are several interesting aspects about the results.
First, we found a substantial effect of top–bottom polarity in the ambiguous displays. However, this the effect of
polarity on reaction times was only apparent on present
trials (t(15) = 3.28, p < 0.006) and not on absent trials
(t(15) = 0.90, p < 0.38). This is understandable. In order
to establish that there is no target present, the participants will have to search through all the items in the
display, with both figure–ground assignments. Consequently, any effect of top–bottom polarity on initial
figure–ground assignment would be minimized. In contrast, target present trials should be influenced by the
initial figure–ground assignment, which in turn is modulated by the top–bottom polarity of the shapes. Targets
would be found faster when they are revealed by the first
figure–ground assignment rather than following a second assignment process.
The second result of interest is that, for exactly the
same (ambiguous) displays, the polarity effect on present
trials was larger in Experiment 4 than Experiment 3
(one-sided t(30) = 1.9, p < 0.035). Since the ambiguous
displays were generated in exactly the same way for both
experiments, the enhanced effect probably reflects the
fact that participants could use top-down knowledge
about the targetÕs color in Experiment 3, but not Experiment 4, although differences in response strategies between the experiments can not be totally excluded. In
Experiment 3, foreknowledge of the targetÕs color
should have helped to bias figure–ground assignment,
counter-acting any bias from the top–bottom polarity
of the shapes. When the color bias was reduced (in
Experiment 4), a stronger effect of top–bottom polarity
emerged.
Thirdly, we note that RTs for the unambiguous displays are in the same ball park as those for the ambiguous displays in Experiment 3 (t(30) = 1.32, p < 0.196).
This is consistent with our suggestion that figural search
is comparable to visual search.
The combination of results from Experiments 3 and 4
also discounts two alternative explanations that might
be suggested for the observed effects of top–bottom
polarity in figural search.
The first of these is that the results reflect an effect of
top–bottom polarity on symmetry detection per se (i.e.
that it may simply be the case that it is easier to detect
a symmetrical target when it has a relatively wide base
J. Hulleman, G.W. Humphreys / Vision Research 44 (2004) 2779–2791
and a narrow top than vice versa). Indeed, in another
paper (Hulleman & Humphreys, 2004) we have shown
that there actually is at most a 10 ms advantage for
the detection of vertical symmetry in a single wide-base
stimulus relative to a wide-top stimulus. A much larger
advantage would be necessary to explain the 100 ms difference we found in Experiment 3. Moreover, even if we
would assume that the reaction time advantage for symmetry detection in wide-base stimuli could be larger in
the ambiguous displays we have used in Experiments 3
and 4, the results of Experiments 3 and 4 cannot be
brought into register using differences in symmetry
detection alone. An explanation purely based on differences in symmetry detection would predict a smaller effect of top–bottom polarity in Experiment 4. In
Experiment 3, the participants know the target color
and will therefore only select the items in that color
(the fact that the RTs in the unambiguous condition
of Experiment 4 are on a par with the RTs in Experiment 3 suggests that this is the case). Hence, in Experiment 3, the reaction time difference between wide base
and wide top targets should be maximal, because the
reaction times in either condition will solely be based
on the ÔquickÕ wide base items and the ÔslowÕ wide top
items, respectively. In Experiment 4, the participants
do not know the target color beforehand. Hence, they
may frequently select the ÔwrongÕ target color. This will
reduce the reaction time difference between the widebase and the wide-top condition, because the reaction
times in both conditions will be based on a mix of the
ÔslowÕ wide-top and ÔquickÕ wide-base items. However
we observed exactly the opposite: the difference between
the wide-top and wide-base conditions increased in the
target present condition of Experiment 4 compared with
Experiment 3.
Second, the effect of top–bottom polarity cannot be
attributed to a speed–accuracy trade-off. It is true that
there were more errors on target present than on target
absent trials, particularly for the displays with ambiguous figure–ground relations in Experiment 4. This pattern, with more errors on target present than on target
absent trials, is quite common in visual search tasks.
Typically the result is taken to reflect the early termination of search on target present trials, prior to the target
being detected (e.g. Chun & Wolfe, 1996). In our experiments this early termination of search is most likely to
have occurred when the participants assigned the region
that contained the target to be ground. The resulting figural area would contain four asymmetric search items.
After finishing the search of these four items, the participants probably were tempted to terminate their search,
rather than attempt to reverse the figure–ground assignment and search the four remaining items. This
mind set would have been encouraged by the nonambiguous stimuli, that effectively contained only four
search items.
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The result does not detract from the effects of top–
bottom polarity on performance however. The critical
aspect of the data is that there are more errors for wide
top items than for wide base items. Here, the error pattern follows the RT pattern exactly. There are less errors
in the quick wide base condition, irrespective of whether
the general error level is higher, like on present trials, or
lower, like on absent trials. We suggest then that participants conduct a search task based on a representation
parsed into figure and ground regions, and that this regional assignment is influenced by the top–bottom
polarity of the shapes. It could be argued that the RTs
in Experiment 4 are too long to reflect the influences
of figure–ground assignment. However, visual search
for symmetry is very slow (see also Olivers & Van der
Helm, 1998). So, even when the appropriate figure–
ground assignment takes place, to enable the target to
be selected, RTs will remain long and likely affected
by the number of figural regions in the display. In addition, there will be large costs on performance if the
ÔwrongÕ color is initially interpreted as defining the figural regions (e.g., for wide top targets, where the figural
assignment might first be given to the wide base
regions).
6. General discussion
We have reported four experiments into the effects of
the top–bottom polarity of spatial regions on figure–
ground organization. In Experiment 1, wide base regions were reported as figure, in preference to wide
top regions, in a substantial majority of participants.
In Experiment 2, a VSTM-task suggested that participants prefer a wide base shape as a figure. Experiments
3 and 4 provided additional evidence for the influence of
top–bottom polarity on figure–ground assignment.
In Experiment 3 participants were set to detect a symmetric target in a given color, when there were ambiguous figure–ground relations between the parts of the
display. Despite participants being set to code the display on the basis of color, we found effects of the top–
bottom polarity of the stimuli on performance. It was
harder to detect a target with a wide top relative to a target with a wide base. In Experiment 4, we examined the
same task with the same ambiguous stimuli. This time
however, participants were not given information about
the targetÕs color beforehand. Under these conditions
the effects of top–bottom polarity on performance were
far larger than in Experiment 3, where any biasing effect
of polarity on figure–ground assignment could be counter-acted by foreknowledge of the targetÕs color. This
interaction between polarity and foreknowledge of the
targetÕs color (in Experiment 4 vs Experiment 3), is difficult to explain if polarity only influenced symmetry
detection. However, the results from Experiments 3
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J. Hulleman, G.W. Humphreys / Vision Research 44 (2004) 2779–2791
and 4 fit with the proposal that top–bottom polarity
influences figure–ground assignment.
In sum, our results converge in suggesting that top–
bottom polarity is one factor which, along with others,
contributes to figure–ground coding. Indeed, the combined influence of factors is demonstrated by the contrasting strength of the polarity effects in Experiments
3 and 4. In Experiment 3, the influence of top–bottom
polarity was moderated by top-down parsing by color
into figure and ground.
Prior studies of figure–ground coding have not indicated that top–bottom polarity is a critical factor,
though factors such as object familiarity (ÔdenotivityÕ
in Peterson & GibsonÕs, 1994 terms) have been shown
to play a part and object familiarity is likely reduced
by inversion (e.g., see Jolicoeur, 1985). It might be argued that the wide base stimuli we used in our experiments look like the silhouettes of evergreen trees. Since
these are familiar shapes, this might have driven figure–ground assignment, rather than top–bottom polarity. However, there are several difference between the
wide base regions and evergreen trees. First, the silhouettes of evergreen trees tend to be vertically symmetrical,
due to their exposure to gravity. All wide base regions in
Experiments 1 and 2, and most wide base regions in
Experiments 3 and 4 were asymmetrical. Second, the silhouette of an evergeen tree tends to be a smooth curve,
unlike the serrated envelopes of the wide base regions in
our experiments. Third, because evergreen trees are
trees, they actually have a narrow base: their stem sticks
out from underneath the branches. Moreover, it could
be argued that the wide top shapes look like the tornade
shapes that are familiar from weather programs and disaster movies. Clearly there was no advantage for these
forms. Another argument against familiarity as an
explanation of our results are the stimuli used by Peterson and Gibson (1994). Their displays contained regions
with easily recognisable shapes that had to compete
against regions with no reasonable object interpretation
at all. Even under those more ideal circumstances
Peterson and Gibson (1994) reported for the condition
where both the high and the low denotative regions were
asymmetric (comparable to our Experiment 2) only a
61% preference for the high denotative regions. It seems
inappropriate to call either the wide base or the wide top
stimuli in Experiment 2 highly denotative, suggesting
also that the influence of familiarity on the outcome of
Experiment 2 was minimal.
As we have noted, Vecera et al. (2002) proposed that
there is a tendency to code the lower region of a stimulus
as figure and the upper as ground, when a display segments into distinct upper and lower regions. From this
it might be argued that, here, the bottom part of the
shapes was strongly weighted in figure–ground organization, so that there was a bias to code a stimulus as figure if it had a wide/stable bottom part. So, rather than a
new figure–ground cue, the top–bottom polarity should
be considered as an extension of the lower region cue.
However, in our case, whole shapes (top, as well as bottom parts) were coded as ÔfigureÕ, so there was no simple
parsing of the display into bottom and top halves. Indeed, unlike Vecera et al. (2002), the bottom half of
the displays contained ground as well as figural elements. Furthermore, the difference in the distribution
of the area between wide base and wide top stimuli
was relatively minor. In Experiment 2, the centres of
mass were, on average, respectively some 6% of the
height of the stimuli below and above the midline of
the displays. So, most of the time, the centres of mass
of the wide base stimuli were in the fifth horizontal strip
from the bottom, just under the midline of the display.
Describing this situation as lower region probably
stretches beyond the point where it is useful to use the
concept. This is especially the case the stimuli with 16
horizontal strips (used in the other experiments), where
the centres of mass fell even closer to the middle.
Now, when given a choice as to whether a Ôwide baseÕ
or a Ôwide topÕ stimulus is upright, independent observers routinely choose the Ôwide baseÕ stimulus. Thus the
effect of top–bottom polarity on figure–ground assignment may well reflect a more general bias in visual coding, favoring objects that appear stable when aligned
with the gravitational upright.
It is important to point out that our argument for the
effects of top–bottom polarity on figure–ground coding
comes from several sources. First, we found the bias
when we employed an explicit reporting task. Second,
we observed the same bias when we employed a
VSTM-task. Third, we also found the effect of top–bottom polarity in a novel task that depends on figure–
ground assignment, but is not directly contingent on
introspective factors. This convergence of results not
only supports the conclusion that top–bottom polarity
is a figure–ground cue, it also suggests that figural search
has some credence as a method in figure–ground research. We propose that figural search is a welcome
addition to the instruments at the disposal of researchers
interested in figure–ground assignment.
Acknowledgment
This work was supported by the UK Medical Research Council.
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