Allocentric Versus Egocentric Spatial Memory in Adults with Autism Spectrum Disorder
Journal of Autism and Developmental Disorders
Allocentric Versus Egocentric Spatial Memory in Adults with Autism Spectrum Disorder
Melanie Ring 0 1 2 3 4
Sebastian B. Gaigg 0 1 2 3 4
Mareike Altgassen 0 1 2 3 4
Peter Barr 0 1 2 3 4
Dermot M. Bowler 0 1 2 3 4
Melanie Ring Melanie.ring. 0 1 2 3 4
@city.ac.uk 0 1 2 3 4
0 Donders Institute for Brain , Cognition and Behaviour , Radboud University Nijmegen , Nijmegen , The Netherlands
1 Present Address: Department of Child and Adolescent Psychiatry, Medical Faculty of the Technical University Dresden , Dresden , Germany
2 Autism Research Group, Department of Psychology , City , University of London , Rhind Building, Northampton Square, London EC1V 0HB , UK
3 Department of Psychology , City , University of London , London , UK
4 Department of Psychology, Technische Universität Dresden , Dresden , Germany
Individuals with autism spectrum disorder (ASD) present difficulties in forming relations among items and context. This capacity for relational binding is also involved in spatial navigation and research on this topic in ASD is scarce and inconclusive. Using a computerised version of the Morris Water Maze task, ASD participants showed particular difficulties in performing viewpoint independent (allocentric) navigation, leaving viewpoint dependent navigation (egocentric) intact. Further analyses showed that navigation deficits were not related to poor visual short-term memory or mental rotation in the ASD group. The results further confirm the need of autistic individuals for support at retrieval and have important implications for the design of signposts and maps.
Spatial navigation; Autism spectrum disorder; Allocentric; Egocentric; Visual short-term memory; Mental rotation; Task support hypothesis
Autism spectrum disorder (ASD) is a developmental
disorder that is characterised by difficulties in the areas of social
interaction and communication and restricted and repetitive
(American Psychiatric Association 2013)
Individuals with ASD show a heterogeneous cognitive profile
with a specific pattern of intact and compromised processes
Electronic supplementary material The online version of this
supplementary material, which is available to authorized users.
(Boucher and Bowler 2008; Boucher et al. 2012)
Rote memory, which is the ability to learn material without
understanding its meaning, was found to be a strength of
individuals with ASD
(e.g. Hermelin and O`Connor 1975)
Spared performance was also reported in tests measuring
(Bowler et al. 1997)
, immediate cued recall (e.g.
Mottron et al. 2001) and recognition memory
et al. 1998)
. Given that these procedures provide more
support at test, Bowler et al. (1997) proposed the ‘task support
hypothesis’ stating that ASD individuals show less
difficulties when they can rely on external sources of support
recognition rather than free recall of items; Bowler et al.
2004, 2015; Gaigg et al. 2008; Minshew et al. 1992; Mottron
et al. 2001; Toichi and Kamio 2003)
. Bowler et al. (2011) in
their relational binding account have argued that the reason
for this difficulty on unsupported test procedures is a reduced
capacity for relational binding in ASD, i.e. difficulties
linking elements of experience to one another or to their spatial
or temporal context to form a coherent episodic
representation in order to enable flexible retrieval of that
information. These relational binding difficulties become apparent
when ASD participants are asked to remember the context
of an item presentation, for example temporal
et al. 1996; Bigham et al. 2010; Gaigg et al. 2014; Minshew
and Goldstein 1993; Ring et al. 2016)
et al. 2014, 2004; Cooper et al. 2015; Ring et al. 2015, 2016;
Semino et al. 2017)
or other types of context information
(e.g. Hala et al. 2005; Lopez and Leekam 2003; Maister
et al. 2013; O’Shea et al. 2005)
Another capacity that is reliant on relational binding is
spatial navigation. One way for spatial navigation to be
successful is that one needs to create an abstract map
representation of the environment which depicts the relation among
goal location, object cues and travel direction in the
environment. Neurologically, relational binding has been
demonstrated as a capacity of the hippocampus
and also spatial navigation has been shown to be
at least in part dependent on the hippocampus (e.g. Bohbot
et al. 2004). In particular, allocentric navigation or “shifted
view-point representation” refers to navigation dependent on
the processing of the relations among goal and landmarks
independent of a single view-point and is regulated through
the (right) hippocampus
(Bohbot et al. 2004)
navigation or “same view-point representation” on the other
hand describes navigation using the self as a reference for
navigating a route and is regulated through the caudate
(e.g. Bohbot et al. 2004; Hartley et al. 2004)
Following the relational binding account, one would expect
specific difficulties with allocentric navigation in ASD, yet
few studies have examined this issue.
Investigating processes like memory and spatial
navigation in ASD is important since they can give hints to the
aetiology of the disorder through comparison with patient
populations with other disorders such as amnesia
(Feigenbaum and Morris 2004)
. In addition, difficulties in memory
and spatial navigation impact on an individuals’ way to cope
with the demands of daily life and ultimately affect their
quality of life, which has been reported to be reduced in
(e.g. Gilotty et al. 2002; Liss et al. 2001; Van Heijst
and Geurts 2015)
. Previous studies of spatial navigation in
ASD show inconsistent results, with two studies reporting
no differences between groups
(Edgin and Pennington 2005;
Caron et al. 2004)
, one study finding an overall navigation
difficulty in ASD (Lind et al. 2013), and two studies
finding specific difficulties in allocentric conditions
Hoffmann 1990; Lind et al. 2014)
, which is what would be
predicted following the relational binding account (Bowler
et al. 2011). It is important to note that only two of these
earlier studies compared allocentric and egocentric conditions
within one study
(Lind et al. 2013, 2014)
. The paradigm
used by Lind et al. (2013, 2014) presented participants with
target objects on a virtual island that participants were asked
to navigate to. In an egocentric/visible condition, locations
of target objects were marked by flags, whereas in an
allocentric condition, participants had to relocate the objects
without the flags. For this task, one could argue that
presenting participants with flags as cues to the hidden objects can
be seen as task support and since people with ASD typically
perform better on supported tasks
(e.g. Bowler et al. 1997,
, this may have been the reason for their better
performance on the visible trials. The present study was designed
to address this gap in the existing literature by equating
egocentric and allocentric conditions on their relational binding
In order to systematically compare adults with and
without ASD on allocentric and egocentric spatial
navigation, we adapted a computerized version of the
Morris Water Maze, in which participants were asked to find
a hidden platform in a virtual swimming pool, which
was surrounded by object cues
(Feigenbaum and Morris
. One of the previous spatial navigation studies in
ASD referred to above also used a water maze paradigm
(Edgin and Pennington 2005)
. However, the results of that
study are inconclusive because the authors tested
participants only with a place learning condition, i.e., testing
simple spatial memory that enabled the use of allocentric
as well as egocentric processing
. As a
consequence, ASD participants may have compensated for
potential allocentric problems by using intact egocentric
processing. To overcome this issue, the improved design
Feigenbaum and Morris (2004)
was employed in the
current study, which is described in detail in what follows.
After a familiarisation phase called place learning, where
object cues, platform location and the participant stayed
in the same position across a number of trials, allocentric
and egocentric conditions were presented in which either
object cues or the participant changed their position. In
the allocentric condition, the object cues and the
platform position were fixed, however, the participant moved
around the screen keeping the relations among platform
location and cues constant. In the egocentric condition, the
platform and the participant stayed in the same position
but the object cues changed position to disturb allocentric
processing. Feigenbaum and Morris tested 14 patients with
a right unilateral temporal lobectomy (RTL), 16 patients
with a left sided one (LTL), and 16 healthy control
participants on this task and found that only the RTL group
showed impaired performance in the allocentric condition.
In the current study, two additional conditions (allocentric
and egocentric 2) were added to control for the
possibility that group differences in the Feigenbaum and Morris
study resulted from differences in task features between
the allocentric and egocentric conditions whereby in one
condition the person moved (allocentric 1) and in the other
condition the platform moved (egocentric 1). In the two
added conditions, either the participant moved together
with the platform position (allocentric 2) or the platform
moved with the objects and the participant stayed in the
same position (egocentric 2). In addition, we extended the
number of trials on each task from 8 to 16 to enable better
learning of the platform position. This takes into
consideration that ASD individuals might need more repetitions
to reach the same performance level as TD individuals
(see Bowler et al. 2008)
. Finally, we implemented place
learning as the first condition, followed by the allocentric
and egocentric conditions in counterbalanced order across
participants. Feigenbaum and Morris (2004) always asked
participants to perform place learning followed by the
allocentric condition, which was then followed by another
place learning and the egocentric condition, which may
have resulted in unwanted order effects.
Feigenbaum and Morris (2004)
expected that participants in both groups would show
learning across trials for all conditions and that adults
with ASD would show particular difficulties in allocentric
navigation, leaving egocentric navigation intact. Further,
we expected a similar pattern of results for the two added
conditions with individuals with ASD showing difficulties
in allocentric 2 but not egocentric 2 compared to the TD
group. In addition to the Morris Water Maze task, three
tasks to assess participants’ visual short-term memory and
mental rotation were administered
. This was to explore whether people with ASD
show difficulties with the temporary storage and
manipulation of spatial information per se, which would point to
additional difficulties related to functions based outside the
hippocampus, for example involving parietal brain regions
(Silk et al. 2006; Tadi et al. 2009; Zacks 2008)
the relational binding account
(Bowler et al. 2011)
, we did
not expect differences between groups on tests of visual
short-term memory and mental rotation.
Sample size was determined by reference to previous
studies of this kind and via power calculation.
included 14–16 participants in each of their
three groups of participants. In addition, power calculation
(Faul et al. 2007)
showed that 16
participants in each group would be needed to find the predicted
between-group difference in allocentric navigation with an
effect size of ηp2 = .10 and a power of .95. To increase
statistical power because of the heterogeneity of ASD samples,
26 individuals with ASD (23 men, Mage = 38.81 years, age
range 24–63 years) and 26 TD individuals (18 men, Mage
= 42.12 years, age range 22–61 years) took part. Groups
were matched on gender, X2 = 2.88, p = .09, chronological
age (CA), Verbal Intelligence Quotient (VIQ), Performance
IQ (PIQ) and Full-scale IQ (FIQ) as measured by the third
edition of the Wechsler Adult Intelligence Scale
(WAISIIIUK; The Psychological Corporation 2000; see Table 1)
Participants were randomly selected from a panel of over
50 individuals with whom the Autism Research Group is
in regular contact. Initially, the panel was created through
advertisements in newspapers, job agencies, contacts to
selfhelp groups for individuals with ASD and word of mouth.
In addition, TD participants were recruited through
newspaper advertisements. ASD individuals were all diagnosed
by experienced clinicians according to DSM-IV-TR criteria
aVerbal IQ (WAIS-IIIUK)
bPerformance IQ (WAIS-IIIUK)
cFull-scale IQ (WAIS-IIIUK)
eADOS—Reciprocal social interaction subscale
fADOS total score − communication + reciprocal social interaction
hADOS—stereotyped behaviours and restricted interests. ADOS scores are presented with range in
(American Psychiatric Association 2000)
prior to the study.
In addition, 23 of these individuals were available to take
part in an assessment with the Autism Diagnostic
(ADOS; Lord et al. 1989)
researchers trained to research reliability standards on this
instrument (for ADOS scores, see Table 1). TD individuals were
only included in the study if they were free of psychotropic
medication and had no personal or family history of
neuropathology or psychiatric illnesses. All participants were
born in the UK and spoke English as their mother tongue.
Informed consent was obtained from all individuals before
taking part, they were paid standard university rates for
their participation and their travel costs were paid for. The
experimental procedures outlined below adhere to the ethical
guidelines set out by the British Psychological Society and
were approved by City, University of London’s Research
Materials and Procedure
Participants were tested individually and testing took about
1.5 h. The order of tasks was counterbalanced across
participants, with the ASD and TD members of each matched
pair receiving the same order. Visual short-term memory
and mental rotation tests were either given before or after
the Water Maze task, which was counterbalanced across
Spatial Navigation Task
A computerized version of the Morris Water Maze written in
Microsoft Visual Basic 6 was used to measure spatial
navigation. This was an adaptation of Feigenbaum and Morris’
task (2004). The task was presented on a 19″ touch-sensitive
which was placed horizontally on a table located in a
soundproof room. The table was surrounded by a small area, which
was separated from the rest of the room by beige curtains
placed on the ceiling and hanging from the ceiling forming
a little cubicle to reduce the influence of external distracters
or cues such as windows or features on the walls within the
room to guide navigation. During the task, participants were
asked to stand around the table looking down on the screen
and to place their finger on it. There was sufficient space in
the cubicle to allow participants to walk around the
horizontal screen according to the task instructions. During task
performance, room lights were turned off so that the only
visible light came from the screen. This further reduced the
influence of features in the room. On each trial, participants
were presented with a virtual swimming pool environment.
The display included a blue circle area representing the
water in the pool, which was surrounded by an orange wall
representing the wall around the pool. Outside the pool, a
green area was presented representing grass growing around
the pool area. On the grass, four objects were displayed in
each corner of the screen, namely a chair, a life ring, a towel
and a beach ball (see Fig. 1). The starting point, the location
where participants were supposed to put their finger before
moving it in the pool area, was indicated by a red dot on
the orange wall around the swimming pool. On every trial,
participants were asked to move their finger across the blue
pool area until the platform appeared, which was represented
by a brown box.
Participants were told that their task was to work out and
learn the shortest way towards a hidden platform in the pool
over several trials starting at the starting point and
moving their finger across the blue space without lifting it from
the screen and without crossing the orange perimeter line
until the hidden platform appeared. The position of the
participant’s finger was recorded during the entire experiment.
After three practice trials during which participants learned
how to use the touch-sensitive screen, participants were first
presented with the place learning block and then with the
2 allocentric and the 2 egocentric blocks. Blocks were
presented in counterbalanced order across participants with two
individuals of a matched pair (one ASD and one TD person
with similar IQ) performing the same order.
The starting point changed position on the orange wall in
a random order. Each block consisted of 16 trials each
lasting 60 s. If a participant could not find the platform within
60 s in one trial, a time out message together with the
platform appeared on the screen and the participant was asked to
move their finger to the platform. Each trial was followed by
a distracter task, which consisted of a series of 12 blue
circles (‘bubbles’) that appeared one after the other at random
locations on a black screen and the participant was asked to
‘burst’ the bubbles by touching them. Measures taken were
path length, time to find the target, path angle and
percentage of time in the target quadrant. The target quadrant was
defined as the quadrant where the participants’ path entered
the platform. Control measures taken were: out of pool times
(number of times participants left the pool area), finger lift
times (number of times participants lifted the finger from
the screen), time out times (number of times participants did
not reach the target within 60 s), time before first movement
(time from touching the starting point until the first
movement in the pool area), and the duration of the distracter task
(time for distracter task).
Place learning served as a control condition without any
systematic manipulations taking place. The platform, the
object cues and the participant stayed in the same location
across the 16 trials of the task.
In the allocentric 1 condition (original), the platform and
the object cues were presented in the same locations across
the 16 trials but the participant had to move to another side
of the table after every trial in a fixed randomized order. The
direction of movement was indicated by an arrow on the
screen and the phase ‘Please move to this side’. The
movement could be 90 (in both directions) or 180° and it was used
to disrupt egocentric processing.
The egocentric 1 condition (original) was designed to
disturb allocentric processing in that the platform and the
participant stayed in the same position across the 16
trials, but the object cues rotated in a fixed randomized order
after every trial. Again, the movement could be 90° (in both
directions) or 180°. The participant, however, did not see the
objects rotate; the objects were only presented in their new
rotated order to the participant.
In the allocentric 2 condition, participants stayed in the
same position but the platform moved with the objects so
that the relations among platform and objects stayed the
same. This was to disrupt egocentric processing. The
movement was 90° (in both directions) or 180°.
In egocentric 2, allocentric processing was disrupted in
that the objects stayed in their same positions and did not
relate to the platform position. The platform moved with the
participants’ position, so that the relation between platform
and participants position stayed the same.
Visual ShortT‑erm Memory and Mental Rotation
To measure participants’ visual short-term memory, a
version of the Brooks matrix task
Participants were presented with sentences describing spatial
relations of numbers in a grid. The grid was a 4 × 4 matrix
with 16 squares. The sentences were formulated as prompts
describing in which cells of the grid which numbers were
to be put to encourage mental imagery of the numbers in
the grid cells. Participants were asked to repeat the sets of
sentences verbatim (e.g. ‘In the starting square put a 1. In
the next square up put a 2.’). The task started with sets of
two sentences describing the positions of two numbers in
the grid. The last sets included eight sentences. Participants
were given three trials at every level and the task stopped if
they had got three trials wrong at one level or completed all
eight levels. Dependent variables were the maximum level
achieved (2–8), the number of correct trials (up to 24) and
the number of trials attempted (up to 24).
Participant’s ability for mental rotation was assessed with
the Manikin Task
(Ratcliff 1979; see also: Acker and Acker
and the Mental Rotations test (Peters et al. 1995). The
Manikin Task was adapted with E-Prime software (http://
www.SciencePlus.nl/E-Prime) for presentation on a 15″
screen. Participants` task was to indicate if the depicted
little man on the screen was holding a black disc in his left or
in his right hand. The man was presented with his front or
back to the participant as well as right way up or standing
on his head. Measures of performance were reaction time
and accuracy. Before and after this task, participants’ were
asked to complete a control task to assess their ability to
make simple left/right judgements
(see Ratcliff 1979; Acker
and Acker 1982)
. In that task, participants were presented
with two circles on the screen (one black and one white),
which were separated by a horizontal black line and they
were asked to indicate as quickly as possible if the black
circle was presented on the right or the left side of the
In the Mental Rotations task,
(version A from Peters et al.
1995, paper and pencil test)
participants were presented with
3D objects made from ten blocks, presented from different
angles and their task was to pick two out of four figures that
matched a target figure. Dependent measures were the sum
of credits (1 credit for 2 correct stimulus figures for an item,
no credit was given if the participant chose one incorrect
figure that did not match the target figure) and the number
of trials attempted (out of 24).
The data were analysed using Chi-Squared test for
nominal data, t-tests, repeated measures ANOVAs, point biserial
and bivariate correlations. If the Sphericity assumption was
violated, Greenhouse-Geisser correction (GG) was applied.
In the case of significant differences, Bonferroni-corrected
post hoc tests were conducted. The significance level was
set at .05 for all tests.
Spatial Navigation—Morris Water Maze
All data are presented in Table 2. In addition, to show
learning over trials for the different conditions, Figure S1 in the
supplementary materials presents heat maps showing a
comparison of the paths for each group between the first and
the last trial of every condition. All analyses presented here
focus on the percentage of time spent in the target quadrant
as this is seen as the most suitable measure for this kind of
analysis. The data on all other measures including control
measures for allocentric and egocentric conditions are
presented in the supplementary materials and Tables S1–S3.
Place learning was used to ensure that participants in both
groups were able to use the equipment properly and that they
show learning over trials. The data were analysed using a 2
(Group [ASD, TD]) × 16 (Trial [1–16]) repeated measures
ANOVA, which showed a significant main effect of Trial,
F(8.55,427.52) = 40.30, p < .0001, ηp2 = .45, GG. No Group
main or Group × Trial interaction effects were significant,
Fmax < 1.66, pmin > .20, ηp2max < .04, confirming similar
learning across trials for both groups. Similar results were
found when analysing the data for the three other measures
(path length, time to target, path angle, see Table S1).
Allocentric 1 vs. Egocentric 1
The data were analysed using a 2 (Group [ASD, TD]) ×
16 (Trial [1–16]) × 2 (Condition [allocentric, egocentric])
repeated measures ANOVA. Next to a significant main
effect of Trial, F(8.92,446.23) = 88.31, p < .0001, ηp2 = .64,
GG, as well as a significant Trial × Condition interaction,
F(8.05,402.54) = 74.70, p < .0001, ηp2 = .60, there was also
a significant main effect of Condition, F(1,50) = 13.18,
p < .001, ηp2 = .21, showing that percentage of time spent in
the target quadrant increased and was higher for the
egocentric compared to the allocentric condition for most trials. A
significant Group × Condition interaction, F(1,50) = 4.10,
p < .05, ηp2 = .08, showed that the ASD group spent a shorter
percentage of time in the target quadrant compared to the TD
group in the allocentric (p < .05, Cohen’s d = .59) but not the
egocentric condition (p = .82, Cohen’s d = .06). There was
no significant main effect of Group, F(1,50) = 1.20, p = .28,
ηp2 = .02,
Allocentric 2 vs. Egocentric 2
The data were analysed using a 2 (Group [ASD, TD]) × 16
(Trial [1–16]) × 2 (Condition [allocentric 2, egocentric 2])
repeated measures ANOVA. There was a significant main
effect of Condition, F(1,50) = 28.54, p = .00, ηp2 = .36, with a
higher percentage of time spent in the target quadrant for the
allocentric 2 compared to the egocentric 2 condition.
However, this was the case for both groups as there was no main
effect of Group, F(1,50)= .28, p = .60, ηp2 = .01, or Group ×
Condition interaction, F(1,50) = .36, p = .55, ηp2 = .01.
Because of the slight difference in the number of men
and women in each group who participated in the task and
previous reports of TD women performing worse than men
at spatial navigation
(Astur et al. 2004)
, we investigated
how gender might have affected the results of the current
study. Point biserial correlation analyses showed that there
were significant positive relations between gender and
performance on the allocentric 1 (r = .32, p = .02) and the
allocentric 2 (r = .37, p = .008) conditions indicating that
women performed better than men in both allocentric
conditions. There were no significant relations between gender
and either of the egocentric conditions (rmax < .14, pmin >
.34) making it unlikely that the slight difference in
gender between groups may have hindered the detection of a
between-group difference in performance on the egocentric
conditions. In addition, including gender as a covariate in
an ANCOVA repeating the analyses reported above showed
that the direction of results stayed the same.
Visual ShortT‑erm Memory and Mental Rotation
The data are presented in Table 3, and they were analysed
using independent samples t-tests. There were no significant
differences in any of the measures for any of the tasks.
aOnly 25 TD and 25 ASD individuals completed this task
bOne ASD individual did not complete this task. A further 2 ASD and 1 TD participants were excluded
because they were at chance in discriminating between right and left in the control task. For both tasks, the
remaining participants in both groups were still matched on VIQ, PIQ, FIQ, age (tmax = -.81, pmax = .42,
Cohen’s dmax = .23) and gender (X2max = 2.93, pmax = .09).
Finally, we investigated correlations among allocentric
navigation performance and performance on memory and mental
rotation tasks. Since there were no significant correlations
among any of the measures for either group (see Table 4),
it seems unlikely that performance on the visual short-term
memory and mental rotations tasks may have influenced
performance on the allocentric navigation task.
The primary aim of this study was to explore if ASD
individuals show spatial navigation difficulties particularly
in allocentric spatial navigation. Such a deficit would be
consistent with the relational binding account of autistic
(Bowler et al. 2011)
. To test this, we compared
matched groups of adults with and without ASD on
navigation conditions that either required egocentric or allocentric
(Bohbot et al. 2004)
using a human virtual reality
adaptation of the Morris Water Maze task. We predicted to
find particular difficulties in ASD with forming view-point
independent, allocentric representations. As control tasks
visual short-term memory and mental rotation tasks were
used to measure participants’ ability to process and
manipulate spatial information. We did not expect difficulties in
ASD on these tasks.
Our prediction was confirmed for the two original test
conditions. Only for the allocentric condition ASD
individuals spent less time in the target quadrant compared to
TD individuals. This finding is supported by a number of
other observations. First, there were no differences between
groups in place learning (the baseline condition). Second,
there were no differences between groups in participants’
ability to follow instructions (out of pool, finger lift times)
and speed of learning (time out times). There was also no
difference between groups in how long they took to complete
the distracter task between blocks (bursting the bubbles),
suggesting that both groups experienced the same time
interval between tasks. Finally, consistent with our expectations
no between-group differences were found for the control
tasks of visual short-term memory and mental rotation. The
absence of any significant correlations among allocentric
navigation and visual short-term memory and mental
rotation performance makes it unlikely that these abilities had
any influence on the significant between-group difference in
allocentric spatial navigation performance.
There are a number of possible caveats to the conclusions
drawn from the present findings. These caveats ask for a
cautious interpretation of the results and future research is
needed to confirm them and the conclusions drawn from this
study. First, the allocentric condition of our task may have
been more complex than the egocentric condition which was
reflected in participants’ longer paths and time taken to find
the platform in the allocentric compared to the egocentric
condition. However, the formation of a viewpoint
independent representation of the world is in general a more complex
operation. What is important, however, is the fact that the
allocentric condition was more difficult for both groups, yet
only ASD participants showed diminished performance in
this condition relative to the comparison group. Second, it
might seem surprising that we did not find any differences
between groups in any of the other performance measures
such as time to target or path length. However, these other
measures are not independent of one another and, therefore,
they do not necessarily indicate success in the task. A very
high variation among participants might have obscured any
differences between groups in these performance measures.
Percentage of time in the target quadrant is a measure that
is often used in the literature and it is less vulnerable to
variation between participants because it is expressed as
a percentage. A third limitation may be that more females
were tested in the TD compared to the ASD group. Since it
is known that females show lower performance compared to
males on spatial navigation tasks in TD populations
et al. 2004)
, the slightly higher number of females in our TD
sample may have diminished differences between groups.
This is however unlikely as correlations between task
performance and gender suggest that women performed better
on the allocentric conditions in this study. A fourth caveat
may be that an aerial view on the search area was used which
makes the task less realistic and might require different
processing mechanisms compared to navigation in the real
world. Future studies should, therefore, use real-life
navigation or 3D environments to represent real-life situations
more closely. Despite this last limitation, the Water Maze
task was chosen to be most appropriate since the aim of
this study was to test the relational binding account of ASD
which implicates altered functioning of the hippocampus as
the basis of difficulties in ASD. Moreover,
showed difficulties in allocentric navigation
on the water maze task in a patient population with temporal
lobectomy including the hippocampus.
At first glance, it may also seem surprising that there was
no significant difference between groups in the percentage
of time spent in the target quadrant for the added allocentric
condition (allocentric 2). In the two added conditions, both
groups spent more time in the target quadrant in allocentric
2 compared to egocentric 2. Also, the results suggested
that the egocentric 2 condition was more difficult for both
groups. In this condition, the platform position moved when
the participant moved, which is unnatural and does not
happen in real life because buildings stay where they are in
space. However, both groups could perform this condition
and most importantly the ASD group performed as well as
the TD group which indicates that their spatial awareness in
relation to the environment is sufficiently robust to perform
the task. Allocentric 2 may have put fewer demands on the
ASD group than allocentric 1 during which participants had
to move around the pool while the platform and object
positions remained fixed. When moving around the display area,
the participant saw the display from a different perspective
on every trial and had to mentally rotate the display back
to the original perspective. In contrast, in allocentric 2
participants stayed in their original location while the platform
and the objects changed their position and relations between
platform and object positions stayed the same. Here,
participants did not need to mentally rotate the display because it
was being rotated for them. Possibly, allocentric 1 put higher
demands on perspective taking abilities than allocentric 2.
Indeed in typical participants it has been found that
perspective taking abilities predicted spatial navigation abilities in
a pointing task
(Kozhevnikov et al. 2006)
. Alternatively, by
alleviating the demands for mental rotation, the allocentric 2
condition may have provided more support than allocentric
1 and this additional ‘Task Support’
(Bowler et al. 2004)
may be the reason why difficulties in the ASD group were
only apparent in the unsupported allocentric 1 condition.
Possibly, ASD individuals can overcome their difficulties
under certain environmental conditions
(see also Gaigg et al.
. Differences between allocentric 1 and 2 may also
have resulted from differing task complexity, since ASD
individuals have been shown to struggle when tasks are more
complex (Minshew and Goldstein 1998). Complexity can be
operationalised in terms of the number of relations/bindings
a participant needs to form in each task. For allocentric 2,
between the objects and the
platform position need to be formed (there are no changes
of objects’ positions independently of each other, therefore,
2 binary relations are enough). For allocentric 1, the
participant needs to form a ternary relation between the platform
and object positions and their own position in order to locate
the platform in a given trial. Possibly, ternary as opposed to
are particularly difficult for
(Boucher and Bowler 2008)
Overall our findings add further support to recent
evidence showing that ASD individuals have difficulty with
allocentric spatial navigation as evidenced by spending less
time in the target quadrant of a navigation task
(Lind et al.
. The fact that we could replicate this finding with a
different paradigm suggests that this is a robust effect. Given
that ASD individuals performed similarly or even slightly
better than TD individuals on the visual short-term memory
and mental rotations tasks provides strong support for the
idea that hippocampally mediated processes rather than
more general difficulties with temporal storage and
manipulation of spatial information lead to a deficit in the
allocentric navigation condition. Therefore, our finding expands the
relational binding account in ASD
(Bowler et al. 2011)
spatial navigation and further reinforces the task support
(Bowler et al. 2004)
in a spatial navigation
paradigm. The present findings have important implications for
the design of signposts and maps. Given that individuals
with ASD show unimpaired performance in egocentric
conditions, they might benefit from map displays along roads
and at bus stops that are presented in the direction in which
an individual is walking.
Acknowledgments We would like to thank all the participants, who
have taken part in this research. The first author was supported by an
Erasmus scholarship as well as a travel grant from “Die Gesellschaft
der Freunde und Förderer der Technischen Universität Dresden” to
work on this study.
Author Contributions MR, SBG and DMB conceived of the study,
implemented the design and contributed to the analysis and
interpretation of the results. MA offered critical comments on the design of the
study and contributed to the analysis and interpretation of the results.
PB programmed the task and contributed to the analysis and creation
of heat maps. MR and SBG were responsible for data collection. MR
drafted the manuscript and MA, SBG and DMB provided critical
comments for revisions. All authors read and approved the final manuscript.
Compliance with Ethical Standards
Conflict of interest The authors declare that they have no conflict of
Ethical Approval All experimental procedures outlined involving
human participants were in accordance with the ethical guidelines set
out by the British Psychological Society, they were approved by City,
University of London’s Research Ethics Committee and they adhered
to the 1964 Helsinki declaration and its later amendments.
Informed Consent Informed consent was obtained prior to
participation from all individuals included in this study.
Open Access This article is distributed under the terms of the
Creative Commons Attribution 4.0 International License (http://creativeco
mmons.org/licenses/by/4.0/), which permits unrestricted use,
distribution, and reproduction in any medium, provided you give appropriate
credit to the original author(s) and the source, provide a link to the
Creative Commons license, and indicate if changes were made.
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