ORIGINAL RESEARCH ARTICLE
published: 25 February 2015
doi: 10.3389/fpsyg.2015.00216
Sequential egocentric navigation and reliance on
landmarks in Williams syndrome and typical development
Hannah J. Broadbent 1,2 *, Emily K. Farran1 and Andrew Tolmie1
1
2
Psychology and Human Development, University College London, Institute of Education, London, UK
Centre for Brain and Cognitive Development, School of Psychology, Birkbeck, University of London, London, UK
Edited by:
Mark Blades, University of Sheffield,
UK
Reviewed by:
Dermot Bowler, City University, UK
Inês Bernardino, University of
Coimbra, Portugal
*Correspondence:
Hannah J. Broadbent, Centre for Brain
and Cognitive Development, School of
Psychology, Birkbeck, University of
London, London WC1E 7HX, UK
e-mail: h.broadbent@bbk.ac.uk
Visuospatial difficulties in Williams syndrome (WS) are well documented. Recently,
research has shown that spatial difficulties in WS extend to large-scale space, particularly
in coding space using an allocentric frame of reference. Typically developing (TD) children
and adults predominantly rely on the use of a sequential egocentric strategy to navigate
a large-scale route (retracing a sequence of left–right body turns). The aim of this study
was to examine whether individuals with WS are able to employ a sequential egocentric
strategy to guide learning and the retracing of a route. Forty-eight TD children, aged 5,
7, and 9 years and 18 participants with WS were examined on their ability to learn and
retrace routes in two (6-turn) virtual environment mazes (with and without landmarks). The
ability to successfully retrace a route following the removal of landmarks (use of sequential
egocentric coding) was also examined. Although in line with TD 5-year-olds when learning
a route with landmarks, individuals with WS showed significantly greater detriment when
these landmarks were removed, relative to all TD groups. Moreover, the WS group
made significantly more errors than all TD groups when learning a route that never
contained landmarks. On a perceptual view-matching task, results revealed a high level
of performance across groups, indicative of an ability to use this visual information
to potentially aid navigation. These findings suggest that individuals with WS rely on
landmarks to a greater extent than TD children, both for learning a route and for retracing a
recently learned route. TD children, but not individuals with WS, were able to fall back
on the use of a sequential egocentric strategy to navigate when landmarks were not
present. Only TD children therefore coded sequential route information simultaneously
with landmark information. The results are discussed in relation to known atypical cortical
development and perceptual-matching abilities in WS.
Keywords: Williams syndrome (WS), navigation, visuospatial cognition, egocentric, landmarks
INTRODUCTION
Williams syndrome (WS) is a neurodevelopmental disorder arising from a deletion of around 27 genes on chromosome 7q11.23
(Koehler et al., 2014). Characteristic of WS is an uneven cognitive
profile of relative strengths and weaknesses, with poor visuospatial
skills relative to verbal abilities frequently reported (e.g., Jarrold
et al., 1998). The use of an allocentric spatial frame of reference to guide navigation (coding spatial relationships between
objects external to the self) is particularly problematic for individuals with WS as evidenced on both on small- (Nardini et al.,
2008; Bernardino et al., 2013) and large-scale tasks (Farran et al.,
2010; Broadbent et al., 2014). However, it is currently unclear
whether such spatial difficulties in WS are also evident in the use
of an egocentric frame of reference (coding spatial relationships
between the self and environmental objects) during large-scale
navigation.
In the real world, navigation usually requires the ability to
retrace a route from one location to another, along familiar or
previously learnt paths, only occasionally necessitating knowledge
of short-cuts or an understanding of the allocentric relationships
between locations in a given environment. Indeed, some research
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has argued that even when taking novel short-cuts, a simple egocentric landmark navigation strategy is predominantly employed,
rather than complex allocentric spatial referencing (Foo et al.,
2005, 2007). That said, the extent to which landmarks are used to
facilitate route-learning, and the specific function that they serve,
has been a matter of some debate. Some authors have reported
the importance of environmental landmarks as navigational aids
(e.g., Jansen-Osmann, 2002), while others have found little benefit
of the presence of landmarks, particularly when other strategies,
such as recalling a sequence of left–right turns, are readily available
to the navigator (e.g., Tlauka and Wilson, 1994).
The ability to use landmarks to guide performance on spatial tasks develops throughout early childhood (e.g., Newcombe
and Huttenlocher, 2000; Sutton, 2006). Although a range of ages
have been suggested as to when the ability to use different landmarks emerges, this likely relates to variability in task demands,
the size of environmental space, and the role that landmarks are
given during learning (Waller and Lippa, 2007). In relation to the
development of large-scale spatial knowledge, spatial representations become progressively more complex throughout childhood,
with landmark knowledge conjectured to precede sequential route
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Broadbent et al.
knowledge and global or configurational mental representations,
respectively (Siegel and White, 1975; Cousins et al., 1983). This
developmental acquisition of spatial knowledge is considered to
be mediated by the emergence of low-level cognitive abilities,
with landmark knowledge associated with the development of
recognition-in-context memory, and route knowledge with the
emergence of paired-associative learning (Allen and Ondracek,
1995). Others have concluded that these age-related changes are
associated with a hierarchical development of spatial coding,
rather than a qualitative shift from one stage to the next (e.g.,
Newcombe and Huttenlocher, 2000). This is also in line with
different developmental trajectories for egocentric and allocentric spatial frames of reference as seen in both small- (Nardini
et al., 2006) and large-scale tasks (Bullens et al., 2010), with older
children and adults more able to successfully switch to using an
allocentric frame of reference when the task requires a more global
mental representation of space.
It can therefore be inferred that younger children will rely
on more basic landmark-based spatial strategies by which to
navigate, that do not comprise of allocentric (spatial relational)
information. Cohen and Schuepfer (1980) showed children aged
7 and 11 years and adults a series of slides along a route that
contained landmarks. Although all groups required the same
amount of time to learn the route, when shown the slides of
the maze without landmarks, 7-year-olds made more incorrect
turn choices than 11-year-olds, who in turn made more errors
than adults. The youngest children also recalled fewer landmarks
that were integral to route orientation (i.e., positioned at a correct or incorrect turn). These findings were replicated in the same
age groups using continuous navigation through virtual environments (VEs; Jansen-Osmann and Wiedenbauer, 2004). However,
Jansen-Osmann and Fuchs (2006) argued that the findings of the
two aforementioned studies actually indicate that children and
adults use landmark information in a qualitatively similar way to
enhance way-finding, and that developmental differences in the
use of landmarks are only seen in relation to other aspects of spatial cognition. That is, although 11-year-olds and adults were able
to learn a route in fewer trials than 7-year-olds (both with and
without landmarks), way-finding performance in all groups benefited equally from the presence of landmarks. The findings did,
however, show a developmental difference in landmark knowledge
and orientation behavior. Similarly, when asked to retrace a route,
children aged 6 and 12 years of age were found to benefit equally
from being advised to take notice of landmarks near the route;
although only the older children were able to benefit from being
told to pay attention to distant landmarks (Cornell et al., 1989).
As such, children and adults are seen to use the information provided by (proximal) landmarks to a similar extent to adults for
way-finding behavior, but a developmental difference is seen in
the way in which landmarks are used for other aspects of largescale spatial cognition, with age-related differences in the use of
landmarks dependent on the task demands and type of landmark
available.
On navigation tasks designed to elicit spontaneous navigation
strategies, typically developing (TD) children and adults predominantly rely on a sequential egocentric strategy, recounting the
sequence of left–right body turns to retrace a route (Iglói et al.,
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Sequential egocentric navigation in WS
2009; Bullens et al., 2010). Given the importance of egocentric
spatial coding and use of landmarks as navigational guides, it is
therefore essential to address the way in which individuals with WS
are able to navigate from one location to another along familiar
routes, and which aspects of the environment are the most useful
in aiding successful way-finding.
On a comparable task to that by Bullens et al. (2010), individuals with WS were found to exhibit atypical navigational
performance, indicating that the use of more simple sequential
egocentric strategies may be problematic for this group (Broadbent et al., 2014). These findings suggest instead that individuals
with WS may rely on less efficient navigational methods. One possibility, explored in the present study, is that individuals with WS
use a technique that involves searching for familiar visual scenes
in order to find a target location.
Individuals with WS are able to successfully learn a route both
in virtual and real environments, albeit often at a slower rate than
TD children of comparable non-verbal ability (Farran et al., 2010,
2012a,b). However, to date, this has only been examined in environments in which landmarks have been present. As such, research
investigating the extent to which individuals with WS rely upon
the presence of landmarks to guide learning and the retracing
of a route would provide further insight into the specific navigation strategies employed by this group. More specifically, an
examination into the ability to use a sequential egocentric strategy
when explicitly required to do so (for example, when landmarks
are removed and an individual must rely on their memory of
the sequence of left–right body turns) would be a useful tool
to further identify specific deficits in large-scale spatial cognition
in WS.
To date, there has been a paucity of research examining the
role of landmarks in navigation in WS. In a 6-turn VE, individuals
with WS were able to successfully learn a route using landmarks as
cues to aid way-finding, in line with TD children aged 6–8 years
(Farran et al., 2012a). The study also found that individuals in the
WS group with higher non-verbal ability were able to differentiate
between junction and path landmarks. This was shown by superior memory for junction over path landmarks, and was therefore
indicative of an ability to understand the usefulness of landmarks
at junctions. As a result, the authors concluded that although
individuals with WS are able to form cognitive representations of
landmarks, important landmark knowledge that can be used to
enhance way-finding may only occur with increased maturity of
non-verbal ability.
These findings suggest that environmental landmarks may play
an important role in the development of spatial knowledge in
WS, as seen in typical development. Furthermore, previous findings suggest that individuals with WS may well use visual scenes
within an environment to navigate, including in situations where
TD children are able to apply alternative spatial coding strategies (Broadbent et al., 2014). The extent to which individuals with
WS would rely on the presence of landmarks both for learning
and retracing a route compared to TD children, however, remains
equivocal.
Allocentric spatial coding is associated with preferential activity in the right hippocampal region (e.g., Burgess et al., 2002;
Hartley et al., 2003), with ‘egocentric’ processing associated with
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Broadbent et al.
activation in the fronto-parietal networks along the dorsal stream
(e.g., Seubert et al., 2008; Weniger et al., 2009). However, memory for the sequence of body turns associated with specific
choice points through a route (a sequential egocentric strategy)
may involve other neural networks than those associated with
independent egocentric responses. Indeed, during the use of a
sequential egocentric strategy the left hippocampus is preferentially activated (Iglói et al., 2010). Related, sequential memory is
associated with activation in the hippocampus, particularly during the acquisition of spatial sequences (Rolls and Kesner, 2006).
These findings are in line with cortical activation during sequential route-based navigation in mice (Rondi-Reig et al., 2006). In
light of these findings regarding the neural basis of the use of
different spatial frames of reference and navigational strategies,
alongside findings of atypical brain development in WS, particularly in the hippocampus (Meyer-Lindenberg et al., 2005), it
stands to reason that individuals with WS would exhibit specific difficulties on tasks requiring accurate processing of both
allocentric and sequential egocentric spatial information. However, it remains unclear as to the strategies that individuals with
WS typically use to complete way-finding tasks, and indeed, the
underlying neural mechanisms and cortical structures that are
involved.
The aim of the present study was to therefore examine the
extent to which individuals with WS rely on the presence of landmarks both when learning a route, and when retracing a route
once landmarks are removed following learning, compared to TD
children of comparable verbal and non-verbal ability. In essence,
are individuals with WS able to apply the use of a sequential egocentric strategy (recalling the sequence of left–right body turns),
which is independent of the use of landmarks, to retrace a route
when visual properties of the environment (i.e., landmarks) are
no longer, or have never been, available?
Given the above mentioned discussion alongside findings of
atypical strategy use during spontaneous navigation tasks in WS
(Broadbent et al., 2014), it was inferred that individuals with WS
would have difficulties in developing a sequential egocentric representation of a route that could be used when landmarks were
removed. TD children and adults are able to reiterate the sequence
of body turns through a route to reach a target location (Iglói
et al., 2009; Bullens et al., 2010). However, atypical brain development in cortical regions that subserve spatial coding strategies
such as allocentric and sequential egocentric representations in
WS imply that individuals with this disorder will rely heavily on
landmarks, and to a greater extent even than TD children when
learning a route. Impairments in the use of a sequential egocentric strategy would also be reflected in a difficulty learning a route
that does not contain any visual landmark cues, and would therefore be indicative of a complete reliance on landmarks to guide
way-finding.
With regards to the nature of difficulties in the use of a sequential egocentric strategy in WS, a further aim of this study was to
examine the types of errors made by individuals with WS compared to TD children when learning routes in environments with
and without landmarks. That is, do individuals with WS present
with a similar pattern of errors in environments with and without
landmarks as seen in TD children?
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Sequential egocentric navigation in WS
MATERIALS AND METHODS
PARTICIPANTS
Fifty-three TD children were recruited from two London, UK
primary schools, and separated into three age groups; 5-, 7-,
and 9-year-olds. None of the TD children were known to have
any developmental disorders (as acknowledged by parents and
teachers) and all participants had normal or corrected-to-normal
vision. Twenty-one individuals with WS were recruited from the
records of the Williams Syndrome Foundation, UK. All participants with WS had received a positive diagnosis of WS, based
on a “fluorescence in situ hybridization” (FISH) test for deleted
Elastin gene on the long arm of chromosome 7, as well as phenotypic diagnosis from a clinician. Written informed consent was
obtained from the parents of all participants. Signed individual
consent was additionally collected from participants with WS over
12 years of age. Ethical approval for the study was received through
the Institute of Education London ethics committee.
All TD participants were tested in a quiet room within their
schools, whilst WS participants were tested either at their home
or in a testing room at the Institute of Education, London. Five
participants from the TD groups; 5 years (N = 3), 7 years
(N = 1), and 9 years (N = 1), and three participants from the
WS group had difficulties with the tasks or did not complete all
measures. Data for these participants were subsequently excluded
from the analyses. Therefore, data were analyzed from 48 TD
children [5 years: (N = 16, mean age (years; months) = 5.09,
SD = 0.09, range = 5.03–6.01), 7 years: (N = 16, mean
age = 7.08, SD = 0.02, range = 7.05–8.00), 9 years: (N = 16, mean
age = 9.07, SD = 0.03, range = 9.03–10.00)], and 18 participants
with WS (Mean age = 21.09, SD = 4.07, range = 16.01–32.01).
Verbal and Non-verbal abilities were assessed using the British
Picture Vocabulary Scale-III (BPVS-III; Dunn et al., 2009) and the
Ravens Coloured Progressive Matrices (RCPM; Raven et al., 2003),
respectively.
VIRTUAL ENVIRONMENT
The interactive VE was developed using The Vizard Development
Edition (version 3.0) software program, and presented on a 17”
laptop screen. The VE task presented participants with a 6-turn
maze layout within which individuals were able to navigate using
the arrow keys on the keyboard. Each path was of equal length,
and each decision point consisted of a single left–right T-junction.
Incorrect turns were concealed using T-junctions at the end of
each dead-end path, so that they did not appear visually different
from correct turns when viewed from the decision point. Each participant completed a ‘landmark (LM)’ and ‘no-landmarks (NLM)’
condition, the order of which was counterbalanced across participants in all groups. Two maze designs (layouts A and B) were
employed; these contained identical path lengths, structure, and
wall height, but with different sequences of left–right turns (see
Figure 1). To control for any differences across maze designs, half
of the participants in each group received layout A as the LM condition and layout B as the NLM condition, whilst the other half
received layout B as the LM condition and layout A as the NLM
condition. For consistency, the same set of landmarks was used
for each LM condition, regardless of maze design (A or B), with
comparable configurations.
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Sequential egocentric navigation in WS
FIGURE 1 | Birds-eye-view of virtual environment routes (A,B) used for counterbalancing. Dashed line denotes correct route through maze. Red markers
denote location of distal landmarks when route used for ‘landmark’ condition.
To distinguish between conditions and notify participants they
were learning a different route, the LM condition always consisted of red-brick walls, whereas the NLM condition maze always
contained gray-brick walls, regardless of whether layout A or B
was used. This was kept consistent for all participants so that
LM scenes presented in a ‘visual-matching’ task presented following the LM trials (detailed below), all contained red brick
walls.
There were no time restrictions for completion of any of the
tasks, and navigation speed within the VEs was set to a consistent
pace that initial pilot testing suggested was optimal for participants
in each group to easily traverse the route without disorientation
or boredom.
DESIGN AND PROCEDURE
All participants completed the BPVS-III and RCPM tasks before
any other measures. Participants were then presented with either
the LM or NLM condition VE maze (counterbalanced across
participants in each group). A ‘visual-matching’ and ‘landmark
naming’ task always immediately followed the LM condition for
all participants.
‘Landmark’ condition
In the LM condition, participants were asked to navigate from the
starting position to find a “hidden exit” at the end of the maze
(either layout A or B). Surrounding the maze were 12 distal landmarks (two distinct trees, two distinct lampposts, a playground, a
cityscape, a high-rise building, a house, a traffic light, a red tower,
a shop, and a block of flats), at least two of which were visible
from each path. During the learning phase, participants were first
shown the correct route by following a grass path. On reaching
the exit, a celebratory trumpet sound was played and the program
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window automatically closed. The participant was then returned
to the starting position, without the grass path, for the first learning trial. Here, participants were required to walk the route from
memory. An error was counted if the participant traveled more
than half way down an incorrect path. During the learning trials,
the participant had to navigate through the correct route to the
exit without error on two consecutive trials to reach learning criterion and move onto the test trial. Each participant was given a
maximum of seven learning trials to reach criterion, unless zero
errors were made on trial 7, then eight trials were given. As this
was to check whether learning had occurred within seven trials, if
errors were made on trial 8, data from this trial were not included
in the analysis. This learning criterion was selected based on previous findings in TD and WS that showed if participants had not
learnt a route after this number of trials then they will continue to
have difficulty in successfully learning the route (Broadbent et al.,
2014).
Once the participant had learnt the route successfully (reached
criterion) in the landmark condition, they were returned to the
starting position of the maze, but this time with all landmarks
removed. Participants were then asked to retrace the correct
route to the exit. This single test trial was used to examine the
extent to which participants continued to rely on the use of landmarks for successful navigation following learning, or whether
they were able to use sequential egocentric coding to retrace the
route.
‘No landmarks’ condition
As a control condition, to examine whether participants were able
navigate through a maze that did not have any landmarks to begin
with, participants were also asked to learn a route through the
NLM. Similar to the LM condition, participants were first shown
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Sequential egocentric navigation in WS
the correct route by following a grass path to the hidden exit. Participants then entered the learning phase, without the grass path
and were asked to navigate the correct route, without error. In line
with LM condition learning trials, participants had to navigate the
correct route with no errors on two consecutive trials (maximum
seven trials, unless zero errors on trial 7, then eight trials) to meet
criterion.
the results of parametric analyses are presented. One exception
is for ‘number of learning trials’ in the NLM condition. Here,
data were not normally distributed for any group (Kolmogorov–
Smirnov, p < 0.01 for all). In addition, all WS participants (and
the majority of TD participants) failed to meet learning criterion
for the NLM, and thus reached the maximum trial limit. For this
reason, non-parametric analyses were conducted on this data and
analyzed separately from LM data.
‘Visual-matching’ task
Immediately following the LM condition, participants were presented with a visual-matching task, to examine the ability to
remember the correct visual scenes from the maze. Participants
were shown a series of images from the viewpoint of each of the
six junctions of the maze that they had learned. For each trial, two
images (one correct and one incorrect) were presented adjacent
to each other on the computer screen. Participants were asked
to select which of the two scenes they had actually viewed when
walking through the maze. Incorrect scenes consisted of either
an incorrect configuration (an incorrect spatial layout, but containing the correct landmarks), or included incorrect landmarks
from different parts of the maze (but in the same configuration
as the correctly presented scene). Each correct and incorrect scene
pair was presented twice throughout the task (12 trials), with each
image appearing once on the left- and once on the right-hand-side
of the screen.
‘Landmark naming’ task
To examine whether participants were able to easily recognize and
name each landmark, and therefore, to assess the saliency of each
environmental marker as a potential navigational guide, a landmark naming task was used. Here, each of the twelve landmarks
from the landmark-maze was presented individually on the screen
and the participant was asked to name the object. Items were
scored as correct if the correct name, a commonly used alternative,
or synonym was given.
RESULTS
STATISTICAL ANALYSES
Data were examined for deviations from normality using
Kolmogorov–Smirnov tests (p < 0.05). Given the robustness of
parametric tests to variations of normality (Field, 2009), parametric tests were conducted throughout. Non-parametric equivalents
were also conducted in cases where data for half of the groups were
not normally distributed, with comparable results. Therefore only
VERBAL AND NON-VERBAL ABILITIES
To examine differences across groups on BPVS-III and RCPM
scores, one-way analyses of variance (ANOVA) were conducted
for both measures, with group (four levels: 5, 7, 9 years, and WS)
as a between-subjects factor. Results demonstrated an uneven cognitive profile in WS, characteristic of the disorder (Jarrold et al.,
1998; Martens et al., 2008), with non-verbal abilities significantly
below TD 9-year-olds, and at a level no different from TD 5- and
7-year-olds, compared to relatively higher verbal abilities, significantly greater than TD 5- and 7-year-olds, but not significantly
different from TD 9-year-olds (Table 1).
LEARNING PHASE
To examine route-learning abilities in both the ‘with landmarks’
(LM) maze condition and ‘no-landmarks’ (NLM) maze condition
across groups, Mean number of learning trials taken to reach criterion (two consecutive trials without error) was calculated for
each maze condition in each group. As a more sensitive measure
of route-learning ability, the cumulative number of errors made
across all learning trials for each maze condition was also analyzed. Descriptive statistics for these two dependent variables are
displayed in Table 2.
Number of learning trials to reach criterion
Results of a one-way ANOVA (with Tukey-corrected pairwise comparisons) for number of learning trials on the LM maze (including
the two correct criterion trials), showed a significant effect of
group, F(3,65) = 4.85, p = 0.004, η2 = 0.19. This was due to
the WS group requiring a significantly greater number of trials to
learn the route than TD 7-year-olds and 9-year-olds; p = 0.020
and p = 0.006, respectively. No significant differences were found
between WS and TD 5-year-olds (p = 0.360), or between any TD
groups (p > 0.05 for all).
For the NLM, results of a Kruskal–Wallis test yielded a significant effect of group on number of learning trials, H(3) = 8.43,
Table 1 | Mean (SD) raw scores on BPVS-III and RCPM for each group.
Group
Post hoc a
ANOVA
WS (N = 18)
5 years (N = 16)
7 years (N = 16)
9 years (N = 16)
F (df)
p
BPVSb
128.39 (15.38)
76.19 (6.78)
91.56 (12.85)
120.06 (11.26)
67.39 (3,65)
<0.001
5 < 7 < 9 = WS
RCPMc
20.83 (6.21)
17.75 (2.54)
21.56 (3.97)
28.06 (4.11)
15.05 (3,65)
<0.001
WS = 5 = 7 < 9
aTukey-corrected post hoc tests, ‘=’ refers to no significant difference at 0.05 level, and ‘<’ denotes ‘significantly less than’ (p < 0.01).
b BPVS-III, British Picture Vocabulary Scale-III raw scores.
c RCPM, Ravens Coloured Progressive Matrices (RCPM) raw scores.
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Sequential egocentric navigation in WS
Table 2 | Group means (SD) for measures of performance on learning phase in landmark (LM) and no-landmark (NLM) mazes.
Group
WS (N = 18)
LM
NLM
5 years (N = 16)
7 years (N = 16)
9 years (N = 16)
Number of learning trials (including two criterion trials)
5.17 (1.89)
4.25 (1.84)
3.50 (1.16)
3.25 (1.44)
Number of errors
5.06 (4.35)
3.19 (3.47)
1.44 (1.26)
2.00 (2.19)
7.00 (0.00)
5.75 (1.77)
5.94 (1.48)
5.50 (2.16)
15.94 (3.72)
9.06 (6.65)
7.94 (5.98)
7.81 (6.48)
Number of learning trials (including two criterion trials)
Number of errors
p = 0.038. Post hoc Mann–Whitney tests showed that this was due
to the WS group requiring a significantly greater number of trials
than TD 5-year-olds (U = 90.00, z = –2.81, p = 0.005, r = –0.48),
TD 7-year-olds (U = 81.00, z = –3.08, p = 0.002, r = –0.53), and
TD 9-year-olds (U = 90.00, z = –2.32, p = 0.021, r = –0.39).
No significant differences were found between any TD groups
(p > 0.05 for all).
Number of errors across learning trials
To examine the effects of counterbalancing on mean number
of errors, separate mixed ANOVAs, with between-participant
factor of groups (four levels: 5, 7, 9, and WS) and withinparticipant factors of ‘maze’ (two levels: LM and NLM) included
either a between-participant factor of ‘maze-order’ (two levels; order 1: LM before NLM; order 2: NLM before LM)’ or
‘route-order’ (two levels: A first; B first).’ Given that no significant main effects were found for either ‘maze-order’ (F < 1)
or ‘route-order’ (F < 1), nor were there any significant interactions with either variable (p > 0.05 for all) it was concluded that there were no order effects, and so these variables
were not included in subsequent analyses that examined error
types.
To examine the number and type of errors made during the
learning trials for each maze condition, errors were separated into
three categories, in line with the method used by Farran et al.
(2012a), and included as a within-participants factor in the analyses. Errors were coded as (a) ‘single errors’ (an error that occurred
only once at a specific junction across all learning trials), (b) ‘consolidation errors’ (errors that occurred at the same junction on
more than one learning trial, but not on consecutive trials), or
(c) ‘perseveration errors’ (errors that occurred at the same junction on two or more consecutive learning trials). Mean number of
each type of error made during the LM and NLM conditions are
displayed in Figure 2.
A mixed ANOVA with between-participants factor of ‘group’
(four levels: 5, 7, 9, and WS) and two within-participant factors of ‘maze’ (two levels: landmark and no-landmark) and
‘error type’ (three levels: single, consolidation, and perseverative) was conducted. A significant main effect of group
[F(3,62) = 10.77, p < 0.001, η2p = 0.34] was found, with
Tukey-corrected post hoc comparisons showing this was due to
the WS group making a significantly greater number of errors
than all TD groups (p < 0.05 for all). No significant difference was found between any TD groups (p > 0.05 for all). A
significant main effect of maze [F(1,62) = 89.93, p < 0.001,
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FIGURE 2 | Mean number of each error type made across learning
trials on (A) landmark maze and (B) no-landmark maze conditions for
each group.
η2p = 0.59] was also found with significantly poorer performance on the NLM (p < 0.001). Results also found a significant
main effect of Error Type, F(1.43,88.59) = 44.72, p < 0.001,
η2p = 0.42, with pairwise comparisons indicating a significant difference across all error types (p < 0.001 for all). The analysis
also revealed a near-significant group by maze, F(3,62) = 2.67,
p = 0.055, η2p = 0.11, and significant maze by error-type,
F(1.87,115.94) = 46.22, p < 0.001, η2p = 0.43, and errortype by group, F(4.29,88.59) = 6.99, p < 0.001, η2p = 0.25
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Broadbent et al.
interactions. A significant 3-way maze by error-type by group
interaction was also found, F(5.21,107.74) = 3.98, p = 0.002,
η2p = 0.16, showing that there was a different pattern of errors
seen between the two mazes, that differed across groups. Given
the significant main effects, significant interactions, and difference in number of trials to reach criterion, each maze was analyzed
separately.
The analysis of types of errors made in the LM condition learning trials showed a significant main effect of group, F(3,62) = 4.56,
p = 0.006, η2p = 0.18, with Tukey-corrected post hoc tests showing that the WS group made significantly more errors than the
TD 7 (p = 0.006) and 9 (p = 0.028) year-olds, but were not
significantly different from TD 5-year-olds (p = 0.306). A significant effect of error type was also found, F(1.45,89.82) = 4.25,
p = 0.028, η2p = 0.06. Pairwise comparisons demonstrated that
this was due to significantly fewer consolidation errors than single
or perseverative errors (p = 0.003 for both). However, no significant error-type by group interaction was found, F < 1, showing
that the pattern of errors observed in the LM did not differ across
groups.
Results for the NLM condition also showed a significant main
effect of group, F(3,62) = 7.87, p < 0.001, η2p = 0.28. Here
however, Tukey-corrected pairwise comparisons showed that the
WS group made a significantly greater number of errors than all
TD groups on this maze (p < 0.01 for all). This was different
to performance in the LM condition, in which the WS group
performed in line with TD 5-year-olds, and thus explains the
marginal maze by group interaction. No significant differences
were found across TD groups (p > 0.05 for all). An analysis
of error type in the NLM condition learning trials, also found
a significant main effect of error type, F(1.75,106.41) = 55.18,
p < 0.001, η2p = 0.47, due to a significant difference across all error
types (p < 0.001 for all). In addition, a significant error type by
group interaction was found, F(5.15,106.41) = 6.64, p < 0.001,
η2p = 0.24.
To examine this interaction further, error type was examined
separately across groups. Results of a one-way ANOVA revealed a
significant difference only in mean number of perseverative errors
across groups, F(3,65) = 9.49, p < 0.001. Tukey-corrected pairwise
comparisons showed that this was due to a significantly greater
number of perseverative errors made by the WS group than any
TD groups (p ≤ 0.001 for all). No significant differences across TD
groups were found (p > 0.05 for all).
‘LANDMARKS-REMOVED’ TEST TRIAL
As a measure of the ability to use a sequential egocentric strategy following learning in the landmark-condition, participants
were asked to immediately complete the route one final time,
with all landmarks removed. Mean number of errors made during the test trial was calculated for each group (see Figure 3).
A one-way ANOVA to examine the mean number of errors
made across groups, yielded a significant difference across groups,
F(3,65) = 8.89, p < 0.001, with Tukey-corrected pairwise comparisons showing that the WS group made a significantly greater
number of errors than all TD groups (5 years, p = 0.038, 7 years,
p < 0.001, 9 years, p < 0.001). No significant differences were
found across TD groups (p > 0.05 for all).
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Sequential egocentric navigation in WS
FIGURE 3 | Mean number of errors made during ‘landmarks removed’
test trial for each group.
‘VISUAL-MATCHING’ TASK
Incorrect scenes on the visual-matching task were separated into
those with an incorrect configuration (but with correct landmarks
for that junction) and those that included incorrect landmarks
(but in the correct configuration for that junction). Mean number
of errors (incorrect scene choices made, out of 12 trials) and Mean
number correct were calculated for each group.
Although significantly below ceiling (using one-sample t-tests
with Mean number correct), all groups performed well on this
task, with few errors made [5 years: M = 9.44 (1.67), t(15) = –
6.13, p < 0.001; 7 years: M = 9.63 (1.67), t(15) = –5.69, p < 0.001;
10 years: M = 9.75 (2.69), t(15) = -3.34, p = 0.004; WS: M = 9.22
(1.89), t(17) = –6.22, p < 0.001].
To examine errors across groups, a 2-way ANOVA with a
between-participant factor of group (four levels: WS, 5, 7, and
9 years) and within-participant factor of ‘scene type’ (two levels:
incorrect configuration and incorrect landmark) was conducted.
No significant differences were identified across groups, F < 1,
indicating proficient ability to visually match correct scenes from a
recently learned maze in all groups (see Figure 4 for Mean errors in
each group). However, a significant effect of scene type was found,
F(1,62) = 8.17, p = 0.006, η2p = 0.12, with pairwise comparisons indicating that participants made significantly more errors
when the incorrect visual scene contained an incorrect landmark
compared to an incorrect configuration (p = 0.006).
‘LANDMARK NAMING’ TASK
To examine the saliency of each environmental feature used in the
landmark condition maze, the number of correct or appropriate
labels given for each of the 12 landmarks was calculated for each
group. All landmarks were easily named, with a high number of
correct labels given by each group [Mean (SD)]; WS: 11.83 (0.38),
5 years: 11.50 (0.82), 7 years: 11.69 (0.60), 9 years: 11.94 (0.25).
DISCUSSION
The present study examined the extent to which individuals
with WS rely on the presence of landmarks both for learning
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Broadbent et al.
FIGURE 4 | Mean number of errors (incorrect scenes chosen) on
‘visual-matching’ task in each group. Incorrect scenes are separated into
those that included an ‘incorrect configuration’ and those with an ‘incorrect
landmark.’
and for retracing a route, compared to TD children aged 5–
9 years. On learning a six-turn route in a VE maze with 12
distal landmarks, individuals with WS performed in line with
TD 5-year-olds, although required a significantly greater number of trials and made more errors than TD children aged 7
and 9 years. This finding is in line with that of previous routelearning studies in WS, showing route-learning performance at
a level expected based on non-verbal reasoning ability (Farran
et al., 2010, 2012a). On learning trials in a maze without landmarks (NLM), however, individuals with WS presented with a
significantly higher level of impairment than all TD groups, with
none of the participants in the WS group successfully able to learn
the route. As such, although all groups demonstrated substantially poorer performance on learning a maze without landmarks
compared to one with landmarks, the negative impact on learning without visual cues for navigation was seen to a greater
extent in individuals with WS than all TD groups. This difficulty in navigating without the presence of visual cues was further
substantiated when landmarks were removed following learning
in the LM condition. Here, even having successfully learnt the
route with landmarks to a level comparable with TD 5-yearolds, individuals with WS made reliably more errors than all
TD groups once these were removed, demonstrating a greater
reliance on the presence of visual markers to guide learning
and subsequent repetition of a series of decision points along a
route.
No significant differences were found in performance across
the three TD groups on measures of route-learning in either maze
condition, nor on number of errors made following the removal
of landmarks. This absence of a developmental difference on these
tasks is indicative of, not only a high level of route-learning ability by 5 years of age, but also the capacity to fall back on the
use of a sequential egocentric navigation strategy when required
from at least 5 years. This is, in part, counter to earlier findings
of age-related changes in a reliance on landmarks to make correct
turns at decision points along a newly learnt route (e.g., Cohen
Frontiers in Psychology | Developmental Psychology
Sequential egocentric navigation in WS
and Schuepfer, 1980; Jansen-Osmann and Wiedenbauer, 2004).
The use of proximal landmarks in the above-mentioned studies, compared to the use of distal landmarks in the present study
may underlie these different findings, particularly given that distal (global) landmarks may have allowed participants to develop a
single, integrated representation of the route (Ruddle et al., 2011),
resulting in less reliance on landmarks, even in the youngest group.
Alternatively, given that the age range in the present study did not
extend as high as in previous studies, it is possible that the addition of an older TD group here may have yielded improvements
with age. That said, the present results are in line with findings that
young children use landmark information to enhance way-finding
to the same extent as older children and adults (Jansen-Osmann
and Fuchs, 2006). In addition, the present findings alongside previous findings (Bullens et al., 2010; Broadbent et al., 2014) suggest
that the use of sequential egocentric coding is a viable navigation
strategy that can be used by children as young as 5 years of age.
This is akin to the spontaneous navigation strategy predominantly
employed by typical adults on similar route-learning tasks (Iglói
et al., 2009).
The high level of ability to successfully retrace a route observed
in TD children following the removal of landmarks begs the
question of whether participants in these groups were simply
remembering a verbal sequence of left–right turns to complete
the route, and were thus unfazed by the change in environmental appearance. There are three arguments to counter this. First,
children aged 5 years have difficulty in the use and representation
of ‘left/right’ spatial terms (Landau and Hoffman, 2005) and so
successful execution of this strategy would have been particularly
problematic in this group. Second, errors (albeit very few) were
observed following landmark removal in all TD groups, indicating
the role of landmarks at some level in supporting the development
of spatial knowledge in these groups. Third, all TD groups performed highly on the visual-matching task, demonstrating that
they had attended to and encoded this information for use in wayfinding, a process that would not be necessary had they solely
relied upon verbally labeling the left–right sequence. It can be
inferred therefore that during learning in TD children, but not in
individuals with WS, a sequential egocentric representation of the
temporal order of bodily turns was developed simultaneously to
the paired-associative learning of directional responses to specific
landmarks.
The use of a sequential egocentric strategy in which the temporal sequence of body turns is encoded, requires cognitive demands
corresponding to those required for episodic or procedural memory (Packard and McGaugh, 1996; Iglói et al., 2009), and is
associated with activation in the left hippocampus (Iglói et al.,
2010). Given the known cortical atrophy associated with WS
that includes the hippocampus (Meyer-Lindenberg et al., 2005),
it stands to reason that spatial encoding that is typically supported
by these neural networks would be impaired in this disorder.
Indeed, structural and functional abnormalities in the hippocampal region in WS are likely associated with not only impairments
in the use of an allocentric spatial frame of reference in WS
(Broadbent et al., 2014), but also with difficulties in the use of
a sequential egocentric representation, as identified in the present
study.
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Broadbent et al.
Examining the categorization of errors provided further insight
into the nature of impairments in the use of a sequential egocentric strategy in WS. In particular, the high number of perseverative
errors in the WS group, compared to other error types and to
performance by all TD groups reflected a difficulty in WS in
learning a 6-turn sequence of turns. This difference may simply reflect the natural outcome of the scoring criteria when a
high total number of errors are made (e.g., during the NLM).
At a behavioral level, perseverative errors have been previously
noted in WS during navigation tasks (Mandolesi et al., 2009;
Farran et al., 2012a). This is indicative of difficulties inhibiting
previous incorrect responses and is supported by findings that
individuals with WS fail to engage cortical and subcortical structures in the frontostriatal regions that mediate response inhibition
(Mobbs et al., 2007). In the current study, however, a significantly greater number of perseverative errors in WS compared
to TD groups was not identified during learning in a maze with
landmarks. Alternatively, the presence of visual cues in the LM
condition may have supported the formation of cognitive representations of landmarks to guide way-finding in the WS group,
leading to fewer perseverative errors. In contrast to the present
findings, Farran et al. (2012a) found a high number of perseverative errors in WS. The use of proximal landmarks in the
Farran et al. (2012a) study and the use of distal landmarks in
the present study may provide the crucial comparison for future
research.
The substantial impairments in WS on tasks that required
sequential egocentric coding suggest that individuals with this
disorder instead rely on the presence of landmarks to navigate,
and to a greater extent even than TD children of comparable
non-verbal ability. Successful use of landmarks for way-finding
on a previously traversed route requires storage of visual information at decision points, even if the sequential order of these
choice points are not encoded. As such, if individuals with WS
rely on the use of a visual-matching strategy to navigate, it is
reasonable to surmise that they would score highly on tests of
scene recognition. This hypothesis was supported in the current
study, showing that participants in this group were successful at
identifying correct visual scenes from the maze with landmarks.
This is in line with findings from an individual with bilateral
hippocampal damage who presented with spatial impairments
in allocentric and context-dependent episodic memory, but was
able to recognize scenes from a VE environment, suggesting that
visual pattern-matching is not associated with the hippocampus (Spiers et al., 2001). Previous research in WS has also shown
that some perceptual abilities may be relatively unimpaired. For
instance, although individuals with WS are typically impaired on
block construction tasks (e.g., Bellugi et al., 1988), performance
on perceptual components of similar tasks are at the level of
mental-age matched controls (Rondan et al., 2003; Deruelle et al.,
2006).
On the visual-matching task, the finding that incorrectlandmark scenes were more difficult to determine than incorrectconfiguration scenes was not anticipated; an outcome that was
particularly unexpected in WS, given the known difficulties with
coding configurational information in this group (e.g., Nardini
et al., 2008; Bernardino et al., 2013). However, this distinction may
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Sequential egocentric navigation in WS
have been related to differences in the ability to detect changes in
fine and coarse visual information. For instance, in the incorrectlandmark scenes, the general outline of the scene would have
been similar to the correct layout, making it more difficult to
disambiguate between correct and incorrect choices than with
changes to coarse information, as seen in incorrect-configuration
scenes. However, it is difficult to make robust conclusions from
this task, particularly given that in some scenes more landmarks
were visible than in others, meaning that scenes were not matched
for level of difficulty. An alternative method for future studies using such visual-matching tasks should therefore include an
incorrect-landmark and incorrect-configuration version of each
scene for comparison. That said, it is important to note the high
level of accuracy in all TD groups and the WS group on both
scene-types, indicating that all groups were able to use the visual
information from the environment to guide way-finding by some
means.
CONCLUSION
Individuals with WS demonstrate a reliance on visual landmarks
for route-learning and way-finding, to a greater extent than TD
children of comparable non-verbal ability. All participants with
WS failed to learn a route that did not contain landmarks, which
required the development of a representation of the temporal
sequence of body turns. When learning a route with landmarks,
TD children, but not individuals with WS, were able to simultaneously develop a sequential egocentric representation of the
route to aid way-finding in situations such as when landmarks
were removed. Individuals with WS instead likely relied on a
visual-matching strategy by which to navigate, which is susceptible to errors following changes to the physical presentation of
the environment (i.e., the removal of landmarks). Impairments
in memory processes involved in episodic spatial events such as
remembering the sequence of bodily rotations through a route is
in line with atypical development in associated cortical regions in
WS. These findings provide insight, not only into the impairments
in WS in large-scale spatial cognition, but into the strategies that
may be commonly employed by individuals with this disorder to
support way-finding, when typical strategies and egocentric and
allocentric spatial frames of reference are not available to them.
ACKNOWLEDGMENTS
This research was supported by funding from the Economic
and Social Research Council (ESRC) and the Williams Syndrome
Foundation, UK to HB. We would like to thank all the individuals
with Williams syndrome and their families who were involved in
the study. Thanks also go to the children of Branfil Primary and St
Mary’s Primary school who took part in the research. Thanks also
go to Alice Alberici for assistance with data collection.
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Conflict of Interest Statement: The authors declare that the research was conducted
in the absence of any commercial or financial relationships that could be construed
as a potential conflict of interest.
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Sequential egocentric navigation in WS
Received: 13 November 2014; accepted: 12 February 2015; published online: 25
February 2015.
Citation: Broadbent HJ, Farran EK and Tolmie A (2015) Sequential egocentric navigation and reliance on landmarks in Williams syndrome and typical development. Front.
Psychol. 6:216. doi: 10.3389/fpsyg.2015.00216
This article was submitted to Developmental Psychology, a section of the journal
Frontiers in Psychology.
Copyright © 2015 Broadbent, Farran and Tolmie. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The
use, distribution or reproduction in other forums is permitted, provided the original
author(s) or licensor are credited and that the original publication in this journal is cited,
in accordance with accepted academic practice. No use, distribution or reproduction is
permitted which does not comply with these terms.
February 2015 | Volume 6 | Article 216 | 11