Cognitive Brain Research 6 Ž1998. 351–360
Interactive report
Males and females use different distal cues in a virtual environment
navigation task 1
Noah J. Sandstrom ) , Jordy Kaufman, Scott A. Huettel
Department of Psychology: Experimental, Duke UniÕersity, Durham, NC 27708-0086, USA
Accepted 14 December 1997
Abstract
The study of navigational ability in humans is often limited by the restricted availability and inconvenience of using large novel
environments. In the present study we use a computer-generated virtual environment to study sex differences in human spatial navigation.
Adult male and female participants navigated through a virtual water maze where both landmarks and room geometry were available as
distal cues. Manipulation of environmental characteristics revealed that females rely predominantly on landmark information, while males
more readily use both landmark and geometric information. We discuss these results as a possible link between recent human research
reporting hippocampal activation in spatial tasks and animal work showing sex differences in both spatial ability and hippocampal
development. q 1998 Elsevier Science B.V.
Keywords: Hippocampus; Sex differences; Spatial ability; Virtual environments; Water maze; Wayfinding
1. Introduction.
Sex differences in spatial navigation have been widely
reported in rodent species. Specifically, males have often
been shown to perform better than females on spatial
navigation tasks that require the use of distal cues. These
tasks include the Morris water maze ŽMWM. in which
animals search for a hidden platform in a large pool of
water and the radial arm maze in which animals search for
food rewards Že.g., w17,33,35,41x; though see w7,30x.. For
example, when naive rats are trained in the MWM, male
rats typically show more rapid acquisition than female rats.
In addition, when the hidden target is removed after training and rats are allowed to swim freely in the pool, males
exhibit a stronger preference for the area previously containing the target than do females w29,34,36x. There are a
number of factors which have been shown to influence the
appearance of such sex differences. These factors include
hormonal fluctuations associated with the estrus cycle
Žw11,39x; though see w6x. and prior experience with the
maze w30x. Another factor which differentially influences
)
Corresponding author: Fax: q1 Ž919. 660 5726; E-mail:
noah@psych.duke.edu
1
Published on the World Wide Web on 27 January 1998.
0926-6410r98r$19.00 q 1998 Elsevier Science B.V. All rights reserved.
PII S 0 9 2 6 - 6 4 1 0 Ž 9 8 . 0 0 0 0 2 - 0
the performance of males and female rodents on tests of
spatial navigation is the availability of different types of
cues. For example, data from radial arm maze studies
indicate that male rats encode predominantly geometric
information Že.g., room shape. while female rats appear to
encode both geometric and landmark information Že.g.,
objects in the room. w40,41x. Although a variety of factors
influence the performance of male and female rodents on
spatial navigation tasks, there do appear to be fundamental
differences in the ways males and females use spatial
information.
Human experimental studies also suggest that males
may perform more proficiently than females on some tasks
requiring spatial skills Žfor reviews see w15,24x.. For example, adult males perform better on mental rotation tests and
the Piagetian Water Level task w14,23x. Sex differences in
spatial ability have also been reported in preadolescent
children w20,21x. The spatial skills most often tapped in
these tasks, however, are non-navigational Že.g., testing
spatial rotation ability.. Relatively few studies have examined sex difference on navigational tasks, but these studies
do report a sex difference with males performing better on
tests of route learning and direction giving w5,12,38x. Sex
differences have also been reported in the cognitive representations of a studied two-dimensional Ž2D. environment
with males forming a more accurate representation of the
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N.J. Sandstrom et al.r CognitiÕe Brain Research 6 (1998) 351–360
Euclidean or geometric properties and females forming a
more accurate representation of the landmarks w12x. Furthermore, self-report measures indicate that males and
females use different navigational strategies w23x.
There are, however, a number of procedural difficulties
inherent in the study of human navigation. To study realworld navigation, one is typically required to examine
navigation through large-scale three-dimensional Ž3D. environments such as neighborhoods or college campuses
w1,9,10,22,29x. Such environments are often very familiar
to participants and the characteristics of real-world environments are not easily controlled or manipulated. Rather
than studying navigation through neighborhoods or buildings, some recent attempts to study human spatial memory
and navigation have employed real-world analogs of the
MWM and radial arm maze constructed to such a size as
to maintain the subject-to-environment proportions of the
animal tasks w13,28x. For example, Overman and colleagues used a 61 meter outdoor circle, adapting a campus
athletic field, to model the MWM for human participants
w28x. When large-scale outdoor environments such as this
are used to study human navigation, experimenters cannot
readily control or manipulate existing cues and landmarks
Že.g., watertower, building, trees.. Without the ability to
modify such environments, researchers’ flexibility in experimental design is significantly reduced. One obvious
way to gain control over cues is to reduce the size of the
testing area such that it fits inside a confined area allowing
greater experimental control over landmarks and geometry.
Overman and colleagues adopted this approach when testing children in a smaller analog of the MWM Ža 3.6 m
diameter pool. surrounded by a curtain and located in a
large room w28x. Though this study reported developmental
changes in navigational ability there were no apparent sex
differences in performance. Potential differences in cognitive representations or cue use Žlandmark vs. geometry.,
however, were not examined and it might have been the
case that both males and females efficiently located the
target but did so using different spatial cues.
One alternative to the use of real-world environments in
the study of human navigation involves the use of maps or
model environments. For example, Galea and Kimura required males and females to learn a route through a town
drawn on a large piece of paper w12x. The streets on this
map were labeled with names and other landmarks Žhouses,
ponds, cars, bridges, etc.. were represented by drawings on
the map. The elements of such an environment can be well
controlled by the experimenter Žroads can be altered, buildings addedrdeleted, etc.., but it is not clear that learning a
route through a 2D drawing of an environment utilizes the
same spatial skills as navigation. Rather than moving
within the environment, participants view an abstracted
representation of the environment. Performance in such
map learning studies is often measured by the number of
trials required to learn a specific route, the number of
landmarks recalled during a test following acquisition, or a
map extrapolation test w12x. Alternatively, participants may
be required to draw or verbally describe a route through
the previously studied environment w37x. Though experimenters have much greater control over map or model
environments, the navigational abilities measured may be
confounded by other factors such as map reading ability,
map drawing ability, or communicative proficiency.
To investigate sex differences in human navigation, we
employ computer-simulated 3D virtual environments. Such
environments have recently been shown to successfully
assess human navigational abilities in reasonably realistic
settings that are both novel and well controlled w2–4,18,25x.
In the present study, we used a virtual analog of the MWM
and required adult males and females to search for a
hidden target in a large pool of water. Our results demonstrate that males and females are both proficient at learning
the location of the hidden target but that they are differentially affected by changes in the available distal cues.
These findings suggest that sex differences in human
navigational ability may be a result of differences in the
way males and females encode or represent space.
2. Materials and methods
2.1. Participants
Participants were 48 undergraduate and graduate students Ž24 males and 24 females. from the Duke University
community who either received course credit or were
compensated $5 for participation in the 30 minute session.
Prior to beginning the experiment, each participant was
randomly assigned to one of three treatment conditions:
Stable Landmark, Geometric, or Random Landmark. These
conditions are described below. Eight males and eight
females were assigned to each of the treatment conditions.
2.2. Apparatus
Three-dimensional virtual environments were constructed using Build, a CAD-like engine Ž3D Realms Entertainment, Garland, TX.. These environments were presented to participants using a commercially available video
game ŽDuke Nukem 3D, 3D Realms Entertainment, Garland, TX.. Environments were displayed on a 21 inch
monitor at a high resolution Ž800 pixels = 600 pixels..
Participants viewed the monitor at a distance of approximately 55 cm, thereby creating a field of view of approximately 37.58 horizontal and 30.08 vertical. Movement was
controlled with a joystick ŽSidewinder 3D Pro, Microsoft
Corp., Seattle, WA. which allowed participants to move
forward and backward as well as turn left and right. Both
speed of movement through the environment and turning
rate were controlled through the joystick.
N.J. Sandstrom et al.r CognitiÕe Brain Research 6 (1998) 351–360
Fig. 1. The MWM virtual environment used in the Training phase. Ža. The top–down Ž2D. perspective indicates part of the training environment in the editor used to create the environments. Visible are the
pool Žlarge circle., platform and surrounding barrier Žsmaller interior circles., and two landmarks. Žb. An example perspective of a participant running in 3D mode. For clarity, the 3D view is slightly higher
than the actual perspective of a participant in the maze and shows the barrier surrounding the target. During training the barrier did not rise until the participant touched the target inside.
353
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N.J. Sandstrom et al.r CognitiÕe Brain Research 6 (1998) 351–360
2.3. Virtual enÕironments
Two basic environments were constructed for the present experiment: the Obstacle Course and the Morris Water Maze ŽMWM.. The Obstacle Course was used primarily to introduce participants to this type of virtual environment interface and to familiarize them with the controlling
equipment. It consisted of Ž1. a large open room where
participants were encouraged to move about freely and to
practice manipulating the joystick, and Ž2. a timed course,
where participants followed a path through a collection of
rooms connected by narrow hallways that zigzagged from
room to room. The timed course required participants to
negotiate large obstacles, barriers, and tight turns.
The second environment was based on the MWM. Our
adaptation of this environment consisted of a room with a
large circular pool of water Žapparent size s 29 m in
diameter; apparent sizes were determined by assuming the
maximum speed of the participant to be a brisk walk of 2
mrs.. Participants were allowed to move freely within the
pool, although their viewpoint was more akin to wading
than to swimming. Hidden under the surface of the water
was a small circular target Žapparent size s 3.5 m in
diameter. that, when stepped on, caused both a surrounding barrier to rise out of the water and a short piece of
music to play. Fig. 1a depicts one of the MWM environments from a top–down design perspective while Fig. 1b
is a 3D view of that environment similar to the participant’s
view.
A standard MWM environment, used by all participants
in the Training phase of the experiment, provided both
geometric information Ži.e., the surrounding room was
trapezoidal. and landmark information Ži.e., four unique
landmarks were placed in the room.. Three other environments were created for the Testing phase. In the Stable
Landmark environment, the shape of the room was octagonal Žthereby providing very little geometric information.,
but the landmarks were available in the same locations as
in the training environment. In the Geometric environment,
the shape of the room remained trapezoidal thereby providing substantial geometric information, but no landmarks
were available. In the Random Landmark environment, the
shape of the room remained trapezoidal, but the landmarks
were moved randomly throughout the room from trial to
trial. A practice MWM environment was also created in
which the target was fully visible and located in the center
of the pool. In this condition, neither geometric nor landmark information was available, but the target area was
made visible by painting it a highly contrasting color.
2.4. Protocol
2.4.1. Practice.
After informed consent was obtained, participants were
seated in front of the monitor and were presented the
joystick. In the first phase of the experiment, participants
navigated through the Obstacle Course. This familiarized
them with the virtual environment interface and tested for
any pre-existing differences in joystick ability or perception of the environment. Participants began in the freemovement area and were instructed to move about the
room until they felt comfortable with the joystick. They
were then told to exit the room and complete the timed
course as quickly as possible. After completing the obstacle course, participants began the Visible Target trial.
Participants all started from the same location at the edge
of the pool, facing away from the center of the pool. They
were instructed to move directly to the highly salient target
platform in the center of the pool. Upon reaching the
visible target, they were informed that, for the remainder
of the experiment, their task would be to find a similar
target that would be hidden in a different pool location.
Furthermore, they were told that the target location would
remain the same on each of the remaining trials.
2.4.2. Training
The second phase of the experiment consisted of six
trials in which participants searched for the hidden target
in the standard MWM environment. In this environment,
the room was trapezoidal in shape Žthereby providing
geometric information. and four distinct landmarks were
placed in fixed positions in the surrounding room Žthereby
providing landmark information.. Prior to this set of trials,
participants were told to navigate to the hidden target as
quickly and accurately as possible. Each trial began at a
different location along the edge of the pool but never
started in the quadrant of the pool that contained the
hidden target. After reaching the target, participants were
allowed five seconds to move around on the platform
before the trial was ended. There was an intertrial interval
of approximately 30 s, during which time no aspect of the
environment was viewed as it was removed from the
computer monitor.
2.4.3. Testing
Immediately after completing the Training trials, participants began the Testing phase. Participants were informed
that, for the next six trials, the hidden target would be
located in the same location within the pool as during the
Training trials, but that some aspects of the environment
may be changed from trial to trial. They then navigated to
the hidden target in either the Geometric, Random Landmark, or Stable Landmark conditions as described above.
Again, participants were allowed five seconds to move
around on the platform before the trial was ended and the
intertrial interval was approximately 30 s.
All trials throughout the experiment were recorded for
later analysis. Latency to find the target as well as the path
navigated were recorded for each trial.
N.J. Sandstrom et al.r CognitiÕe Brain Research 6 (1998) 351–360
355
3. Results
3.1. Practice
Latency to complete the obstacle course was analyzed
using a two-factor ANOVA Žsex = testing condition..
There was a significant effect of sex on latency to complete the obstacle course w F Ž1,42. s 8.79, p - 0.01x, with
males completing the course in a mean of 137 s and
females completing the course in a mean of 147 s. There
was no significant effect of testing condition Ž p ) 0.05.,
indicating that the joystick abilities, as measured by the
obstacle course, were roughly equal across eventual test
conditions. Furthermore, sex and testing condition did not
interact Ž p ) 0.05..
The latency required to complete the visible target task
was analyzed using a similar two-factor ANOVA. There
was a significant effect of sex w F Ž1,42. s 6.80, p - 0.05x
with males and females requiring means of 12 s and 14 s,
respectively. Neither the main effect of testing condition
nor the interaction between testing condition and sex was
significant Ž ps ) 0.05.. In summary, males’ latency was
significantly less than females’ in both practice tasks,
although the difference was small in magnitude and did
not interact with testing condition. Closer observation of
recorded trials indicated that females experienced a short
delay at the onset of the trial before moving in the water
maze. Furthermore, several female participants verbally
expressed some confusion as the view at the onset of the
trial was of the surrounding room rather than the pool
Žthey were looking over the edge of the pool.. Once
participants began to move, however, all went directly to
the target. A two-factor ANOVA on the latency to reach
the visible target after movement was first initiated re-
Fig. 3. Performance during training. Mean adjusted latency to find the
hidden target for males and females during the Training phase. Latency in
seconds is presented as a function of trial number.
vealed no effect of sex Ž p ) 0.05., supporting the suggestion that females simply took longer to begin this trial due
to a short delay at the trial onset.
3.2. Training
Typical swim paths on training trials are presented in
Fig. 2. It is clear from these paths that participants developed a knowledge of the location of the target platform as
evidenced by the development of efficient search strategies. Raw latency scores were adjusted for each participant
by subtracting the minimum possible latency to reach the
target from the raw latency to reach the target for each
trial. This adjustment results in a measure of deviation
from optimal performance for each trial. The mean ad-
Fig. 2. Typical swim paths over the six training trials. The target area is indicated on this figure, but it was not visible during the trial.
N.J. Sandstrom et al.r CognitiÕe Brain Research 6 (1998) 351–360
356
justed latency of males and females to find the hidden
target on the Training trials is presented in Fig. 3. A
three-factor repeated-measures ANOVA was used to analyze the adjusted latency score across the six training trials
as a function of sex and experimental condition. This
analysis revealed a significant main effect of trials
w F Ž5,210. s 18.00, p - 0.001x, indicating improved performance as trials progressed. Both sexes improved from a
mean adjusted latency of approximately 56 s on the first
trial to near-perfect performance Žmean adjusted latency
4.0 s. on the last trial. There was no effect of sex on
overall performance Ž p ) 0.05., nor was there an interaction between sex and trial number Ž p ) 0.05.. The effect
of testing condition was not significant and it did not
interact with any other factors Žall ps ) 0.05..
3.3. Testing
Fig. 4 presents typical swim paths on test trials. Overall,
males performed better than females in the two conditions
where landmark information did not predict the target
location ŽGeometric and Random Landmark., but males
and females performed equally well when landmark information was available and reliable ŽStable Landmark.. The
mean adjusted latency to find the platform during the
Fig. 5. Performance during testing. Median adjusted latency of males and
females during the Testing phase in the Stable Landmark condition, the
Geometric condition, or the Random Landmark condition. Within each
condition, latency is presented as a function of trial block, either Trials
1–3 or Trials 4–6.
Testing trials is presented in Fig. 5. The three panels
represent the three testing conditions: Ža. Stable Landmark,
Žb. Geometric, and Žc. Random Landmark. Furthermore,
the six trials were divided into two blocks ŽTrials 1–3 and
Trials 4–6.. Within each block, each participant’s median
Fig. 4. Typical swim paths over the six test trials. The target area is indicated on this figure, but it was not visible during the trial.
N.J. Sandstrom et al.r CognitiÕe Brain Research 6 (1998) 351–360
adjusted latency was used as an estimate of his or her
performance.
A three-factor repeated-measures ANOVA analyzed the
median adjusted latency scores across the two blocks of
trials as a function of sex and testing condition. A significant main effect of sex w f Ž1,42. s 13.46, p - 0.001x, indicated that males required less time to locate the target than
did females. There was a significant main effect of testing
condition w F Ž2,42. s 13.86; p - 0.001x, with post hoc LSD
tests revealing that each testing condition was significantly
different Žin latency. from the others Žall ps - 0.05.. The
effects of sex within each testing condition were analyzed
with planned comparisons. Furthermore, post hoc LSD
tests evaluated sex differences within each block of trials.
For the Stable Landmark condition, there were no significant differences between males and females Žall ps )
0.05.. However, in the Geometric condition, males were
significantly faster than females w F Ž1,42. s 8.32, p 0.01x, with a post hoc test revealing a significant difference
between the sexes on the second block Ž p - 0.05.. Males
were also faster than females in the Random Landmark
condition w F Ž1,42. s 7.90, p - 0.01x and post hoc tests
confirmed that this difference was significant on both
blocks Ž ps - 0.05..
For both blocks of trials, females were faster in the
Stable Landmark condition than in either of the other two
conditions Ž ps - 0.05., which were not different from
each other Ž p ) 0.05.. For the first block of trials, males
took significantly longer in the Random Landmark condition than in the Stable Landmark condition Ž p - 0.05.,
with performance in the Geometric condition not differing
from the other two conditions Ž ps ) 0.05.. On the second
block, males’ performance was not significantly different
in any of the conditions Ž ps ) 0.05..
4. Discussion
In this study, we demonstrate the utility of inexpensive
commercially available virtual environments in the systematic study of human navigation. Novel 3D environments
were created in which the experimenter had complete
control over all cues. When tested in an environment
analogous to the MWM often used in the study of rodent
spatial navigation, humans performed in a fashion similar
to rats by showing reduced latencies to the target with
repeated trials and a dependence on distal environmental
cues. These findings are similar to those of Jacobs, Laurance, and Thomas who demonstrated that adult humans
rely on information from the surrounding virtual environment to locate a target hidden in an large arena w18x.
Although both males and females are able to learn the
task, they differ in the extent to which they rely on
particular types of cues. During the Testing phase, males
and females performed similarly in the Stable Landmark
condition; in this condition, the geometric information was
357
not useful but landmark information was available and
predictive. However, when landmark information was not
available ŽGeometric. or did not accurately predict the
target location ŽRandom Landmark., the performance of
males was less adversely affected than the performance of
females. Females were unable to learn an adequate strategy
for quickly locating the target in the Geometric condition
and the performance of females was severely disturbed by
the presence of unreliable landmark cues in the Random
Landmark condition. Males, in contrast, were not significantly disrupted by the absence of landmarks ŽGeometric.
and performance was only transiently disrupted by the
presence of unreliable landmark information ŽRandom
Landmarks..
These differences in latency indicate differential cue use
in the virtual environment. Both males and females were
able to develop effective strategies to find the hidden
target when landmark information was readily available, as
in the Training trials and the Stable Landmark testing
condition. However, removal of the landmark information
was more disruptive to the females. This suggests that
although both sexes may have used landmark information
to guide their search for the platform, the males were
better able to adapt their search strategy when required to
make use of geometric information. The data from the
Random Landmark condition supports this suggestion. The
impairment of females’ performance during the first trials
indicates that they may have been attempting to use the
randomly moving landmarks without much success. Males,
in contrast, were better able to employ geometric aspects
of the environment. Thus, not only do males and females
differ in their self-reported use of navigational strategies
w23x, but they also show differential dependence on certain
cues when those cues are manipulated by the experimenter.
One unexpected finding was that males navigated
through the obstacle course and solved the visible platform
trial faster than females. Although the sex differences
found in these practice trials are significant, we believe
that they are unrelated to the sex differences apparent in
the test trials. Our analysis of latency on the obstacle
course trial and on the visible platform trial revealed that
there was no significant effect of the testing condition to
which the participants were assigned. Thus, sex differences
present during the obstacle course and visible platform
trials cannot account for the interaction of sex and cue
availability during testing. We believe that the latency
differences on the obstacle course are the result of an
initial discrepancy in joystick experience. The path on the
obstacle course was marked with arrows and required a
series of very sharp turns which may have been more
difficult for the female participants who had slightly less
experience using a joystick. It is unlikely that this difficulty in making tight turns adversely affected performance
in the water maze, however, as there was no demand for
tight turns and participants rarely made them. Furthermore,
a closer analysis of the visible platform trials revealed that
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N.J. Sandstrom et al.r CognitiÕe Brain Research 6 (1998) 351–360
the sex differences in latency were a consequence of short
delays in starting that task by the female participants.
These findings indicate that sex differences in performance
during practice trials did not likely influence the differences reported for test trials.
To a large extent, our findings are consistent with those
from animal studies of sex differences in navigation. Using
a radial arm maze, Williams and colleagues manipulated
the geometric characteristics of the room surrounding the
maze Žvia changes in the position of a large curtain. and
varied the location of available landmarks w41x. Their
findings indicate that male rats attend primarily to the
global shape of the environment while female rats attend
to multiple environmental cues including geometry and
landmarks. Human males, in our study, appear to use
landmarks or geometry as the task requires, while human
females appear to be limited to using landmark information with impaired performance when geometric cue use is
required. Thus there are two main differences between the
rat and human results: Ž1. human males successfully used
landmark information while male rats were significantly
impaired when forced to use landmark information, and Ž2.
human females were impaired when forced to use geometric information while female rats were unimpaired when
geometric information was the only available cue Žthough
female rats were impaired when geometric information
was accompanied by unreliable landmark information as in
our Random Landmark testing condition.. The ease with
which human males use landmark information and the
difficulty females encounter when forced to use geometric
information may, however, be an artifact of the experimental setting we employed. In our virtual water maze, the
landmark information appears to be much more salient
than the geometry information. A lack of stereoscopic
depth information, resolution limitations, and lack of
kinesthetic information are all possible contributors to a
less salient perception of depth and geometry w8x.
Although latency improvements are indicative of an
effective navigational strategy, they do not in themselves
provide information concerning the specific swimming
strategy employed. For instance one possible, albeit imperfect, strategy would be to simply rely on a response bias
such as swimming around the pool at a fixed distance from
the edge. Alternatively, one could encode the target location relative to the available distal cues. While both of
these strategies can result in improved performance over a
series of trials, they rely on very different environmental
information. Observation of the recorded trials in this
study indicates that both males and females were likely
guided by distal cues as opposed to simply using a circling
strategy Žfor swim path examples, see Fig. 2.. Research by
others supports this conclusion as humans search longer in
the target quadrant than in other quadrants when the target
is removed from the pool w18x.
Our results provide an important link between recent
human studies implicating hippocampal involvement in
navigation through virtual environments and animal work
demonstrating sex differences in cue use on hippocampally
dependent navigational tasks. Assessment of the neuroanatomical substrates underlying human navigation relies on two techniques: Ž1. the use of modern imaging
techniques such as functional magnetic resonance imaging
ŽfMRI. and positron emission tomography ŽPET., and Ž2.
the study of brain damaged patients. This search for the
neuroanatomical substrates of human navigation has been
guided by animal work implicating the hippocampus and
associated structures with spatial ability in rodents Žfor
reviews see w19,27,32x.. Brain imaging studies have
demonstrated hippocampal and parahippocampal activation
in humans navigating through complex virtual environments w3,25x as well as activation when imagining navigation through a previously learned environment w2x. These
studies, however, have not examined sex differences in
navigational strategy or cue use. A recent study of humans
with hippocampal damage has reported impaired performance on a virtual MWM task w4x. In this study, normal
humans and a small sample of humans with temporal lobe
damage were tested in a virtual environment similar to the
present water maze. Their results suggest that damage to
the temporal lobe including the hippocampus severely
impairs spatial navigation. Interestingly, normal females
tested in their paradigm showed longer routes to the target
platform and used a different search strategy, though it is
as yet unclear how differences in characteristics of their
environment Že.g., pool size, ability to see the surrounding
environment, and apparent speed of movement. may have
influenced these findings. Future studies will need to examine the influence of these and other environmental
characteristics in order to more completely understand how
humans navigate in a virtual environment. It is becoming
more clear, however, that the human hippocampus and
associated structures are intimately involved in navigation.
While our findings do indicate that males and females
rely on different environmental cues when encoding or
recalling information on a virtual environment navigation
task, the biological cause of this difference remains unclear. Two influences which are likely candidates for this
finding are Ž1. the actiÕational effect of gonadal hormones
and Ž2. the organizational effect of these hormones experienced early in development. As discussed in the introduction, the performance of female rats has been shown to be
influenced by fluctuations of activational hormones associated with the estrus cycle w11,39x. Similarly, performance
of human females on tasks measuring perceptual-spatial
ability is influenced by the hormonal changes associated
with the menstrual cycle w16x. It is possible that navigational ability is also influenced by hormonal fluctuations,
however these data were not collected in the present study.
Future studies are needed to understand the potential influence of activational hormones on human navigation.
Exposure to gonadal hormones early in development
has also been shown to influence brain development and
N.J. Sandstrom et al.r CognitiÕe Brain Research 6 (1998) 351–360
later navigational ability in animals. Testicular testosterone
and its metabolite, estradiol, exert organizational influences on hippocampal anatomy when experienced within
the first week of life in the male rat w17,26,34x. Female rats
do not experience this perinatal pulse of testosterone and
circulating estradiol is prevented from acting in the female
brain by the presence of alpha fetoprotein which binds
estradiol and inactivates it w31x. This differential exposure
of the male and female brain to neonatal hormones also
alters performance on spatial tasks when animals are tested
as adults w33,36,40x. For example, neonatal castration of
male rats prevents the organizational effects of testicular
testosterone and results in both development of a femalelike hippocampus as well as female-like use of cues when
solving the radial arm maze. Conversely, exogenous administration of testosterone or estradiol to neonatal females
masculinizes hippocampal development and results in the
male-like use of cues. While we have no direct evidence
that these same processes are responsible for sex differences in cue use for human males and females, the similarities in behavioral data suggest that similar biological
processes may be acting in humans as in rats.
Together, this evidence indicates that the hippocampus
and related structures are involved in human navigation
and that males and females use different strategies in
navigational tasks. Continued advances in virtual environment research and imaging studies will likely improve our
understanding of the factors influencing sex differences in
human navigation and in the cognitive representation of
space.
Acknowledgements
This research was supported by funds from the Experimental Psychology Department at Duke University. NJS
and SAH are supported by National Science Foundation
pre-doctoral fellowships. We would like to thank Greg
Lockhead, Warren Meck, and Christina Williams for valuable discussions on this work. In addition, we would like
to thank two anonymous reviewers for useful comments on
an earlier version of this manuscript.
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