Neurobiology of Learning and Memory 78, 79–99 (2002)
A Room with a View and a Polarizing Cue:
Individual Differences in the Stimulus Control
of Place Navigation and Passive Latent
Learning in the Water Maze
Bryan D. Devan,*,†,‡ Herbert L. Petri,† Mortimer Mishkin,‡ Eric M. Stouffer,†
Jonna L. Bowker,† Ping-Bo Yin,‡ Deanne M. Buffalari,‡ and James L. Olds*,‡
*Krasnow Institute for Advanced Study, George Mason University, Mail Stop 2A1,
Fairfax, Virginia 22030-4444; †Laboratory of Comparative Neuropsychology, Department of Psychology,
Towson University, Towson, Maryland 21252-0001; and ‡Laboratory of Neuropsychology,
National Institute of Mental Health, National Institutes of Health, 49 Convent Drive, Room 1B80,
Bethesda, Maryland 20892-4415
Published online March 6, 2002
We investigated individual differences in the stimulus control of navigational
behavior inthe watermaze bycomparing measuresof placelearning in oneenviron-
ment to measures of latent learning (via passive placement on the goal platform)
in a novel environment. In the first experiment, 12 rats were trained to find a
slightly submerged hidden platform at a fixed location in room A for 10 days
(4 trials/day). Fast and slow place learners were identified by their mean escape
latency and cumulative distance to the goal during acquisition. The same animals
were then given a 2-min passive placement on the submerged platform in room B.
Latent learning was assessed by the animal’s escape latency on a single swim trial
immediately following the placement in room B. The results showed that the good
latent learners in room B were not necessarily the fast place learners in room A.
This weak correlation may be related to the fact that some rats swam near the area
in room B that corresponded to the former goal location in room A relative to a
common polarizing cue (i.e., the door/entrance to both rooms). When the view of
the door was blocked in a second experiment a significant positive correlation
between place acquisition and the latent learning test was obtained, although escape
that while place navigation and latent learning via passive placement may involve
some common cognitive-spatial function, other associative (S-S and/or S-R) proc-
esses that occur during place navigation/active movement may be required for
animals to exhibit truly accurate navigational behavior characteristic of asymptotic
escape performance in the water maze. Additional implications for neurobiological
studies using a procedural pretraining design are discussed.
? 2002 Elsevier Science (USA)
This research was supported by a Krasnow Institute postdoctoral fellowship (BDD); NIMH IRP (M.M.); and
funding by the Department of Psychology, Towson University (H.L.P.). We thank Clif Santiago for technical
assistance. We also thank Dr. Robert McDonald and two anonymous reviewers for their comments.
? 2002 Elsevier Science (USA)
All rights reserved.
DEVAN ET AL.
Key Words: spatial memory; place learning; latent learning; procedural training;
cognitive processing; habit formation.
The learning-performance distinction is fundamental to the neurobehavioral assessment
of memory and is essential for demonstrating response-independent cognitive processes.
One way in which the distinction is often made in learning experiments is by the inclusion
of a control group that must perform the same response as the experimental group, but
is not required to learn specific cognitive information. For example, in studies with the
water maze (Morris, 1981), where rats learn to use the allocentric spatial relations among
extramaze distal cues to find a slightly submerged hidden platform (place navigation), a
commonly used control is to train rats in a similar response guided by an intramaze beacon
or visibleplatform (cuenavigation). Thiscontrol mayhelp determine whetherimpairments
after interventions are related to changes in motor, sensory/perceptual, or motivational
functions common to both tasks. The major shortcoming of this approach, however, is
that the performance requirements of the two tasks are in fact not identical. For example,
different motor movements are employed by the animal in the local search for a hidden
platform versus climbing onto the visible platform. In addition, the intramaze cue is closer
(i.e., more visible and tactually salient) to the rat than extramaze cues, and escape to the
above-water versus submerged platforms may have different incentive values. Further,
because acquisition of the standard water maze tasks depends on the performance of an
escape response, stimulus–response (S-R) accounts of learning cannot be ruled out.
Another approach in assessing cognitive memory involves the use a form of response-
independent learning (e.g., Bower & Hilgard, 1981; Gleitman, 1955; McNamara, Long, &
Wike, 1956). Latent learning in the water maze, originally reported by Sutherland and
Linggard (1982), would appear to be one such form (e.g., Sutherland & Dyck, 1984).
Their experimental procedure involved placing a rat on the hidden platform several times
before the start of place training. One group was placed on the platform at the correct
goal location, while other groups were placed on the platform at incorrect locations within
or outside of the experimental room/pool. The correctly placed group demonstrated faster
acquisition than the control groups on several measures of performance, suggesting that
they had passively learned cognitive information independent of S-R associations. In a
later study, Keith and McVety (1988), reported that the magnitude of this latent learning
effect in a novel environment was increased by pretraining rats on the procedural aspects
of the task in another room.
The nature of the performance advantage conferred by passively viewing the environ-
ment from the goal platform has been a subject of some debate. Whereas some have
argued that the experience can produce “instantaneous transfer” (Keith & McVety, 1988;
Keith, 1989), operationally defined as swimming in a direct path from a novel start point
to the goal platform (Morris, 1981), others have pointed out that although the performance
of rats given passive placement is improved compared to that of controls, it does not
reach the level of asymptotic performance shown by rats allowed to swim through the
environment while viewing distal cues (Chew, Sutherland, & Whishaw, 1989; Sutherland,
Chew, Baker, & Linggard, 1987; Whishaw, 1991). The latter position is consistent with
SPATIAL LEARNING AND PERFORMANCE
the fact that rats given standard swim/escape trials can achieve asymptotic performance
even when visual access to distal cues is reduced by switching off the room lights during
the platform interval, i.e., the period spent on the platform following escape (Devan,
Blank, & Petri, 1992; Sutherland et al., 1987), but not when visibility is obstructed while
a rat is en route to the platform (Arolfo, Nerad, Schenk, & Bures, 1994; Sutherland et
al., 1987) or is required to navigate through a novel area of the pool to reach this goal
(Sutherland et al., 1987). Arolfo et al. (1994) switched off the room lights when animals
entered the inner circular area of the pool containing the hidden platform (group L-D)
during acquisition. These animals were severely impaired relative to controls trained in
permanent light (group L). However, when the animals in group L were transferred to
the L-D condition they were only transiently impaired, suggesting that the formation of
a cognitive map under unobstructed viewing/swimming conditions allowed the subsequent
use of path integration mechanisms alone (based on ideothetic, or self-movement, cues)
to navigate under reduced visibility. Indeed, it has been suggested that integration between
vestibular and visual signals may be a prerequisite for efficient navigation in the water
maze (McNaughton et al., 1996; Semenov & Bures, 1989).
The relative contribution of passively viewing distal cues from the goal platform versus
active swimming/viewing is further complicated by individual differences that the animals
may bring to the experimental situation. For example, latent learning results obtained with
the two-room, procedural pretraining design (see above, Keith & McVety, 1988) may be
difficult to replicate (unpublished observations; Jacobs, Zaborowski, & Whishaw, 1989b).
The failure to find latent learning in seven direct replication attempts (Jacobs et al., 1989a,
1989b) suggests that the phenomenon is elusive at best.
ual differences in place navigation and subsequent latent learning (via passive placement
on the platform) in a novel environment. If learning in both situations involves similar
cognitive processes (e.g., Tolman, 1948), then individual differences in performance in
one situation should be positively correlated with those in the other. Alternatively, if the
two tasks involve different processes, then individual differences in performance across
the two tasks should not be correlated or might even be negatively correlated if the
processes interact competitively.
Materials and Methods
The subjects were 12 male hooded rats of the Long Evans strain (Harlan Sprague–
Dawley), weighing 300–350 g (?90 days old) at the start of the experiment. They were
housed singly in hanging wire mesh cages with ad libitum access to food (LabDiet 5001
Rodent Diet) and tap water. Laboratory illumination was set on a 12:12 light/dark cycle
(lights on 0700–1900 h). All behavioral training and testing was conducted during the
light phase (1200–1700 h).
DEVAN ET AL.
Two reinforced steel tanks with their interior surfaces painted white were each located
in a different room (see Fig. 1). Room A (297 ? 458 cm) was slightly wider than room
B (280 ? 458 cm). Room A contained a water tank (171 cm in diameter ? 59 cm high)
that was positioned on cinder blocks, raising it 20 cm from the floor and located slightly
off-center relative to the four walls (distance from west-50 cm, east-73 cm, north-143
cm, and south-155 cm). A bookshelf (304 cm long and 193 cm from floor) was located
on the west wall and a table (77 ? 158 ? 93 cm) with a television set and video monitor
was positioned on the north wall. There was a chair next to the table at the northwest
corner, andpart ofa supportcolumn occupiedthe northeast corner.A sink,towel dispenser,
and pushpin board were located on the south wall adjacent to the entrance and light
switch/timer. Small poster boards with illustrations and text were hung on the upper
middle half of the east wall.
Room B was located next to room A along its west wall. The water tank in room B
was slightly smaller (166 cm in diameter ? 59 cm high) than the one in room A. It was
also positioned on cinder blocks and located off-center with respect to the four walls
(distance from west-108 cm, east-24 cm, north-163 cm, and south-135 cm). A laboratory
counter (310 ? 61 ? 93 cm) and cabinet were located on the west wall. Because there
was less floor space in room B, the tank was positioned closer to the east wall to allow
the experimenter to walk to the north part of the room. A window (139 ? 148 cm) with
closed horizontal blinds and a bedding/food storage bin (88 ? 58 cm) were positioned
on the north wall. A large genome poster and pushpin board with a brain poster were on
platform removal tests following passive placement (room 500 B). In the first experiment, the hidden platform
was positioned at location 1 in both rooms (SW quadrant of room A and NW quadrant of room B). Location
4 represents the equivalent of the former goal location in room A relative to the door/entrance. Abbreviations:
tc-trash can; td-towel dispenser; Lt-light switch/timer.
Schematic of the two rooms/pools used for place acquisition (room 500 A) and the latent learning/
SPATIAL LEARNING AND PERFORMANCE
the east wall. A sink and towel dispenser was located on the south wall, as in room A,
but their position relative to each other was not the same. A chair was placed against the
south wall between the entrance and sink.
In addition to the features described above, small objects unique to each room were
positioned on flat surfaces (i.e., the counter, table, bookshelf, cabinet, sinks, and storage
bin) at fixed locations. Thus, different visual cues were present in the two rooms, with
the exception of some features common to most laboratory environments (door/entrance,
light switch, towel dispenser, chair, and sink). These overlapping cues were either moved
to a different location relative to the entrance in the second room (chair), were generally
less visible from inside the pool (chair and sink), or were close to the door (light switch,
chair, towel dispenser, and sink) and considered part of the “door/entrance” array.
The water tanks were filled to a depth of 32 cm with water. White nontoxic tempera
paint (?100 ml, Best Temp) was added to the water to render it opaque. The temperature
of white plastic piping 13 cm in diameter and 30 cm in height. The platform was filled
with sand and sealed at the top and bottom with white PVC caps. Cameras were recessed
in the ceiling above each water maze. Video input was relayed to a VHS recorder and a
VP118 tracking system (HVS Image Ltd., Hampton, UK) located in the main labora-
Place acquisition (room A).
for a total of 10 days. The top of the platform was submerged 2 cm below the water
surface and was located at a fixed position in the approximate center of the southwest
(SW) quadrant of the tank (Fig. 1). To begin a trial, an animal was gently placed in the
water facing the tank wall at one of four pseudorandomly selected start positions (N, S,
E, and W; not true compass headings) and allowed to swim for 30 s. If an animal had
not found the platform after 30 s the experimenter gently guided it there by hand. Each
rat was left on the platform for 20 s before being removed from the pool. The experimenter
held the animal for an additional 5 s before the start of the next trial from a different
position. The sequence of start positions was varied pseudorandomly each day and was
identical for all rats.
The animals were given four swim trials/day in room A
Passive placement and latent learning test (room B).
place acquisition, the animals were given a 2 min placement on the platform (Keith &
McVety, 1988) located in the approximate center of the northwest (NW) quadrant of the
tank in room B. Following passive placement, the rats were removed from the platform
and held for approximately 5 s before being placed in the tank at the south start point
for the first test trial. The animals were given a total of four swim trials in a manner
similar to place acquisition trials in room A.
On the day after the last day of
Platform removal test.
given one 60-s swim trial in room B with the platform removed from the tank. The
animals were placed in the water facing the tank wall at the east start point.
On the day after the latent learning test, the animals were
DEVAN ET AL.
Performance Measures and Group Assignments
Escape latency and cumulative distance (deviation from a direct path to the goal) were
used to assess learning on swim trials during place acquisition and the latent learning
test. The presentation of escape latency enables direct comparison to previous studies,
whereas cumulative distance may provide a better measure of spatial accuracy (Gallagher,
Burwell, & Burchinal, 1993). Based on these measures the animals were divided into two
groups of six each, labeled Fast or Slow place learners (in room A) and Good or Poor
latent learners (in room B).
Spatial selectivity on the platform removal test was based on Gallagher et al.’s (1993)
proximity measure defined as the subject-to-target distance in centimeters averaged across
all x/y data points, updated every 1/10th s by the HVS analysis program (as standardized
by Richard Baker of HVS Image Inc., 5/98). The average subject-to-target distance was
calculated for locations 1 (the actual platform location in the center of the NW quadrant
of pool/room B) and 4 (the location within the center of the SW quadrant of pool/room
B, corresponding to the former goal in pool/room A; see below). The “former” goal was
defined by the pool calibration used in Room A (i.e., referenced to the pool wall and
quadrants) and was not based on absolute spatial location within Room B. However,
ing) cues associated with it could provide direction information related to the “former”
goal in pool/room A. Similar test conditions have been used to study the influence of
salient cues (e.g., a large movable relay rack) within a single environment (Eichenbaum,
Stewart, & Morris, 1990). Proximity measures relative to both locations in room B were
obtained for the initial response during the probe test (average of data points from the
first 15 s) and the entire probe test period (average of all data points from the full 60 s).
Individual differences in performance during place acquisition in room A and during
the latent learning test following passive placement in room B are shown in Fig. 2.
Animals were assigned to place learning groups (Fast and Slow) based on a split of mean
escape latency scores across the 10 days of place acquisition (Fast means: 6.69, 7.66,
7.96, 7.96, 8.69, and 8.90; Slow means: 8.92, 9.76, 9.99, 11.11, 11.29, and 12.37). This
analysis produced identical group assignments to the split means for both escape latency
and cumulative distance on day 5, midway through acquisition in room A (see Fig. 2).
Animals were assigned to the latent learning groups (Good and Poor) based on the split
means of these same measures during first-trial performance following passive placement
in room B. The latter assessment was restricted to trial 1 because performance on trials
2–4 was not independent of place learning that may occur during active swimming.
members;indeed, nonparametricanalysis showedno relationshipbetween ratesof learning
in the two test situations (Spearman rank test, r ? .00). Three of the fast place learners
were also good latent learners (rats 2, 3, and 9), but the three other fast place learners
(rats 4, 6, and 10) were poor latent learners. Likewise, half of the slow place learners
were good latent learners (rats 7, 8, and 12), whereas the other half were poor latent
learners (rats 1, 5, and 11).
SPATIAL LEARNING AND PERFORMANCE
(bottom) on day 5 of place acquisition in room A (left) and on the latent learning test following passive placement
in room B (right).
Experiment 1: individual differences in escape latency (top) and cumulative distance to the goal
Figure 3 shows the mean escape latencies (top) and cumulative distance to the goal
(bottom) during place acquisition in room A across blocks of four trials for each group.
Three-way ANOVAs revealed significant main effects of Place learning [escape latency:
F(1, 8) ? 22.90, P ? .001; cumulative distance: F(1, 8) ? 18.76, P ? .005], Latent
learning [cumulative distance: F(1, 8) ? 8.63, P ? 0.5], and Trial block [escape latency:
F(9, 72) ? 55.03, P ? .001; cumulative distance: F(9, 72) ? 65.67, P ? .001] and a
significant Trial block x Latent learning interaction [escape latency: F(9, 72) ? 2.07,
P ? 0.5; cumulative distance: F(9, 72) ? 2.11, P ? .05]. Post hoc analyses using Scheffe’s
test showed that the Fast place learning group had shorter escape latencies and shorter
cumulative distances compared to the Slow place learning group on trial blocks 3–5
(ps ? .05). The mean escape latencies for the Fast group were 8.87 (range, 4.80–
13.85 s), 6.87 s (range, 4.33–9.78 s), and 4.37 s (range, 3.73–4.98 s) for blocks 3–5
respectively; the mean escape latencies for the Slow group were 14.90 s (range, 8.45–
21.73 s), 11.38 s (range, 8.35–16.78 s), and 9.19 s (range, 5.58–12.93 s), respectively.
Mean cumulative distances for the Fast group were 428 cm (range, 184–665 cm), 291
cm (range, 184–482 cm), and 179 cm (range, 170–189 cm) for blocks 3–5, respectively,
and for the Slow group were 804 cm (range, 499–1273 cm), 579 cm (range, 282–963
cm), and 431 cm (range, 240–630 cm) for blocks 3–5, respectively. These data show that
DEVAN ET AL.
versus Slow place learning groups (left) and Good versus Poor latent learning groups (right) across the 10 daily
trial blocks (4 trials/day).
Experiment 1: mean (? SEM) escape latency (top) and cumulative distance (bottom) for Fast
the fast place learners reached asymptotic performance more quickly than slow place
learners did. In contrast, on trial block 2 of the place acquisition task, the Poor latent
learning group escaped faster (mean 11.74 s, range 6.53 to 17.10 s) and had a shorter
cumulative distance to the goal (mean 664 cm, range 202 to 1106 cm) than the Good
distance 1127 cm, range 860 to 1317 cm, P ? .05]. These data suggest that performance
following passive placement on the goal in a novel environment may be inversely related
to early place acquisition performance. This possibility was supported by a strong negative
correlation (r ? ?.89, P ? .001) between the mean escape latencies for all 12 rats on
the first block of trials in rooms A and B (Fig. 4).
For the probe test in room B, two-way ANOVAs (Place x Latent learning) were used
to analyze spatial proximity to the passive placement goal (NW quadrant, location 1)
versus the equivalent of the former goal in room A (SW quadrant, location 4). No
significant differences were found for data obtained from the full 60-s test period [Fs(1,
8) ? 2.18, ps ? .05]. Because this could have been due to extinction of spatially selective
behavior, we performed a more restricted analysis, using the data obtained from the first
15 s of the probe test. The swim path for each rat during this time period is shown in
Fig. 5. The analyses revealed no significant group differences in proximity to location 1
[Fs(1, 8) ? 2.19, ps ? .05]. In contrast, the results showed significant group differences
in proximity to location 4 (Fig. 6). The slow place learners and the good latent learners
swam in closer proximity to location 4 than did the fast place learners [F(1, 8) ? 8.26,
SPATIAL LEARNING AND PERFORMANCE
trials in room A (original place training) and the single block of trials in room B (postplacement test).
Experiment 1: relationship between the mean escape latency (in seconds) on the first block of four
p ? .05] and poor latent learners [F(1, 8) ? 12.26, p ? .01], respectively. These results
suggest that individual differences in performance on place acquisition and latent learning
tests can predict the degree of influence exerted by some common cue that defines a
former goal location within a different environment. The possible basis of such stimulus
control is discussed below.
The results of the experiment demonstrate individual differences in place navigation
performance and passive latent learning in the water maze. Although both problems are
thought to rely on a similar cognitive-spatial representation of the environment (Tolman,
1948), the prediction from this assumption of a positive correlation between a subject’s
scores on the two tasks was not supported. The initial place learning groups (fast and
slow) evenly redistributed into the subsequent latent learning groups (good and poor).
Thus, it would appear that the two tasks are not redundant and, in fact, may be sensitive
to individual differences in two separate abilities.
One possibility is that the place learning task places greater demands on the spatial
processing of the relations among distal cues (i.e., map-based, allocentric information)
while the latent learning task places greater demands on the relation of a salient cue (or
group of cues) to the individual’s body. This notion is based on the evidence that some
individuals were strongly influenced by the cue(s) common to both tasks (the entrance/
door to both rooms). On the probe test following the latent learning test in room B, the
slow place learners and good latent learners swam in closer proximity to the spatial
location corresponding to the former goal in room A relative to the door/entrance. We
refer to this behavior as being under the influence of a “polarizing cue” because the door/
DEVAN ET AL.
the platform removal probe test in room B. Location 1 (the passive placement goal location) is in the NW
quadrant. Location 4 (the equivalent of the former goal in room A) is in the SW quadrant.
Experiment 1: the initial segment of swim path recorded for each rat on the first 15 seconds of
entrance was the one salient extramaze cue that remained stable across testing environ-
Another, less salient, cue that remained stable relative to the goal location in room A
was the pool wall. Although it is unlikely that this cue alone could support spatial
discrimination within a novel environment, it may have been used in combination with
at least one other distal cue that provided a directional bearing. Other researchers have
shown that some animals will navigate with reference to pool geometry plus compass
direction, instead of distance and direction to extrapool distal cues, at different times
during place training (Weisend et al., 1995). These findings suggest that, in the present
experiment, the influence of the polarizing cue on the navigational behavior of some
individuals in room B may have been based on a similar combination of pool geometry
with a heading vector derived from the door/entrance. Weisend et al.’s findings also show
that individual differences (related to the sex of the animal) interact with the amount of
training to produce a shift in the stimulus control of navigation. Male rats initially used
pool geometry/compass direction and then shifted to extrapool distal cues. In the present
experiment, however, there is no evidence of a performance advantage on the latent
learning test among individuals that were less influenced by the polarizing cue and
presumably less inclined to use pool geometry/direction in room B following passive
placement. Therefore, even if control of navigational behavior for some rats had shifted
to extramaze cues in the first room, this fact alone was not able to support accurate
navigation following passive exposure to visual cues in a novel environment.
SPATIAL LEARNING AND PERFORMANCE
removal test in room B (the equivalent of the former goal in pool/room A) for Fast versus Slow place learning
groups and Good versus Poor latent learning groups; *P ? .05; **P ? .01.
Experiment 1: mean (? SEM) proximity to Location 4 during the initial 15 s of the platform
door despite the fact that passive placement and the latent learning test were conducted
in a novel environment where the majority of cues were different? The answer may lie
in studies that have shown a strong tendency for animals to “win-stay” (return to a place)
rather than “win-shift” (alternate between places) in the water maze (Whishaw & Pasztor,
2000). Moreover, the presence of some familiar cues in the second room may have had
a blocking effect on the acquisition of new cues and relational information (Biegler &
Morris, 1999; Fenton, Arolfo, Nerad, & Bures, 1994; Rodrigo, Chamizo, McLaren, &
Mackintosh, 1997; Weisend et al., 1995). These findings suggest possible behavioral
control by a noncognitive habit system (Packard, Hirsh, & White, 1989; Petri & Mishkin,
1994). If the place response acquired in the first room was “overlearned” or “stamped
in” during the course of initial training (10 days), then the presence of some similar cues
in the second room may have elicited automatic responses based on S-R learning before
the integration of these older/similiar cues and other newer cues could support allocentric-
based spatial navigation.
The extent to which such S-R behavior would aid or impede performance in the second
room might also depend on other, more subtle, factors. For example, In Experiment 1,
the goal location was moved from the SW pool quadrant in room A to the NW pool
quadrant in room B, and on the first latent learning trial the animals were started from
the South start point. From this start point some animals turned west and passed through
the former goal location en route to the hidden platform in the NW quadrant and, of these
animals, some seemed to slow down and search for the platform as they approached the
former goal, resulting in additional time spent in the former goal location.
DEVAN ET AL.
To investigate these issues further, we conducted a second experiment in which (1) the
view of the door (i.e., the stimulus features of the “polarizing” cue) in both rooms was
obstructed by a white shower curtain that blended with the color of the room walls and
(2) the South start position on the first trial of the latent learning test in room B was now
equidistant from, and symmetrically opposite to, (a) the passive placement goal and (b)
the former goal (in room A) relative to the entrance. We hypothesized that, by eliminating
both the polarizing cue and the possible bias that was present in the first latent learning
trial of Experiment 1, we would reduce if not eliminate the role of S-R learning on
performance and thereby allow allocentric spatial processes to gain greater control.
Materials and Methods
used. Diet, housing, and laboratory illumination were the same as in the first experiment.
white shower curtains were hung from the ceiling to camouflage the door in both rooms.
In room A, one curtain was placed diagonally covering the southwest corner of the room.
The view of the sink and towel dispenser in room A was not obstructed. In contrast, in
room B, two curtains extended along the entire south wall, blocking the view of the sink
and towel dispenser from inside the room.
The apparatus previously described in Experiment 1 was used. In addition,
The procedures used were similar to those previously described with the following
exceptions. During place acquisition, the hidden platform was positioned in the center of
the NE quadrant of the pool in room A. Animals were allowed to swim until they found
the platform or until 60 s had elapsed. Following escape, animals were left on the platform
for approximately 5 s and then returned to their home cage while other animals in a squad
of four were given the same trial. All aspects of passive placement and the latent learning
test in room B were the same as those previously described.
Figure 7 shows the individual differences among animals assigned to Fast/Slow place
learning groups and Good/Poor latent learning groups based on the criteria described in
the first experiment. In contrast to the results of Experiment 1, fast place learners (rats
3, 5, 6, and 7) were also good latent learners, whereas slow place learners (rats 1, 2, 4,
and 8) were poor latent learners. This positive relationship was supported by a significant
Pearson correlation between the mean escape latency for place acquisition and the latent
learning test (r ? .73, p ? .05; see Fig. 8). The bottom graphs of Fig. 7 show the escape
latency and cumulative distance for Slow/Poor and Fast/Good groups across trial blocks.
A two-way ANOVA of place acquisition measures revealed significant Group [escape
latency: F(1, 6) ? 17.96, P ? .01; cumulative distance: F(1, 6) ? 12.84, P ? .05] and
SPATIAL LEARNING AND PERFORMANCE
learning groups and Good/Poor latent learning groups (dashed line in top graphs); the dotted line in the right
graph shows the split mean criterion of Experiment 1. Bottom graphs show the mean escape latency and
cumulative distance to the goal for Fast and Slow place learning groups (also the Good versus Poor latent
learning groups) across the 10 days of place acquisition of Experiment 2.
Experiment 2: individual differences in escape latency that led to the formation of Fast/Slow place
Trial Block [escape latency: F(9, 54) ? 15.73, P ? .001; cumulative distance: F(9,
54) ? 19.82, P ? .001] effects, but no significant interactions (Ps ? .90).
Swim paths on the first trial of the latent learning test following passive placement are
shown in Fig. 9. Three rats (2, 4, and 6) swam through the former location of the platform
in the center of the NE quadrant, whereas the remaining five rats did not cross this
location. In Experiment 1, all 12 rats crossed the “old” location on the first trial of the
latent learning test. Fischer exact test of these frequencies revealed a significant difference
between experiments (P ? .01). Despite this difference, the mean trial 1 escape perfor-
mance on the latent learning test was similar in both experiments (Exp. 1: 13.97 ? 3.36;
Exp. 2: 14.51 ? 2.47; P ? .30), as was the overall mean (? SE) for the block of four
trials (Exp. 1: 8.47 ? 0.98; Exp. 2:9.88 ? 1.29; P ? .90).
Figure 10A shows the percentage of time spent in each quadrant on the first test trial
following passive placement in room B. Two-way ANOVA revealed a significant effect
of Quadrant [F(3, 54) ? 33.78, P ? .001] and a significant Experiment ? Quadrant
interaction [F(3, 54) ? 5.13, P ? .01] but no significant main effect of Experiment
DEVAN ET AL.
training) and room B (postplacement test).
Experiment 2: relationship between the mean escape latency (in seconds) in room A (initial place
(P ? .30). Post hoc tests showed that the time spent in the NW (i.e., the passive placement
goal) quadrant and the SE quadrant did not differ significantly between experiments
(Ps ? .05). Rats in Experiment 2 spent significantly more time in the NE quadrant (the
location of the goal in room A of Exp. 2) than rats in Experiment 1 [F(1, 18) ? 5.41,
P ? .05]. In contrast, rats in the first experiment spent significantly more time in the SW
quadrant (the location of the goal in room A of Exp. 1) than rats in Experiment 2 [F(1,
18) ? 8.79, P ? .01].
test was compared across experiments (Fig. 10B). A two-way ANOVA (Experiment ?
Location) revealed a significant effect of location [F(1, 18) ? 87.35, P ? .001] and a
significant interaction between factors [F(1, 18) ? 10.26, P ? .01]. Animals in each
experiment swam in closer proximity to the former goal location used during place
acquisition in room A compared to the location not used.
The results of Experiment 2 show a positive relationship between place acquisition and
passive latent learning when the view of the door was blocked by a curtain. This positive
correlation is independent of start-goal relations because it is based on the block of four
trials (including all four start points) in room 2. Therefore, the second manipulation
described above (i.e., changing the original goal location in room A) cannot explain the
difference between experiments, leaving only the first manipulation (i.e., eliminating the
stimulus features of the door) as the likely source of the difference.
The positive correlation obtained in the second experiment suggests that place acquisi-
tion and latent learning in a novel environment may be based on some common process
SPATIAL LEARNING AND PERFORMANCE
2-min passive placement in room B. The platform was located in the NW quadrant and the former goal location
was in the NE quadrant.
Experiment 2: swim paths for each rat on the first trial of the latent learning test following the
under conditions that minimize common cue features between environments. However,
the present findings do not rule out some influence of S-R learning because three of the
eight animals did cross the “old” goal location in the NE quadrant. In addition, quadrant
time and proximity analyses showed that behavior was influenced specifically by the
former goal location in room A. One possible explanation is that entry into the rooms
provided at least a minimal directional framework in which path integration (i.e., use of
ideothetic cues) allowed some animals to swim toward the former goal location.
Despite the positive correlation between tasks in the second experiment, performance
on the latent learning test was not improved compared to that in the first experiment.
Therefore, in the first experiment, it is unlikely that the door cue alone had a blocking
effect on the acquisition of new spatial information during passive placement. It is possible
that other contextual cues (e.g., general room/maze geometry, time of day of testing, or
similar routes to the testing rooms) may have interfered with new spatial learning in the
second room. Although this account would not explain the difference in the relationship
between place acquisition and latent learning in the two experiments. Alternatively, re-
moval of the door cue may have been enough to unmask the positive relationship between
tasks in the second experiment; however, room entry may have prevented any overall
improvement in escape performance.
Perhaps optimum expression of latent learning may require more extensive training, at
least for some individuals. The further experience may serve to enhance the spatial
processing of cue relations and/or the integration of movement and sensory-perceptual
processes. The former suggestion is based on evidence that passive placement may not
support spatial discrimination among locations that provide views of similar distal cue
arrays (McDonald & White, 1995) unless the temporal delay between passive exposures
is short(White & Ouellet, 1997).The latter suggestionis based on evidencethat movement
through the environment may be required to produce truly accurate navigation (Chew et
al., 1989; Sutherland et al., 1987; Whishaw, 1991).
DEVAN ET AL.
Experiment 2 (gray bars). (B) The mean proximity to the “old” location (former goal in room A relative to the
entrance) in the first (1) and second (2) experiment. Animals in Experiment 1 swam in closer proximity to
location 1 (their actual former goal) compared to animals in Experiment 2 and vice versa.
(A) The mean percentage of quadrant time for animals in Experiment 1 (open bars) versus
The results obtained in this study provide evidence that the door/entrance of an experi-
mental room may serve as a polarizing cue, influencing subsequent behavior when animals
are required to navigate with reference to distal cues following passive placement on the
goal in a novel environment. The nature of the influence may depend on the experimental
parameters used in a study. For example, in the first experiment of the present study, the
goal platform was moved from the SW quadrant in room A to the NW quadrant in room
B, with the start position at the South point on the first swim trial following the 2-min
passive placement on the goal in the NW quadrant. All rats in the first experiment crossed
the previous goal location (in the center of the SW quadrant) relative to the door/entrance
before escaping onto the platform in the center of the NW quadrant. In Experiment 2,
when the door was hidden and the original goal location was in the diagonally opposite
quadrant (NE), the rats did not cross the “old” location as frequently as in the previous
SPATIAL LEARNING AND PERFORMANCE
experiment although they did spend more time in the former goal quadrant (NW) and
less time in the quadrant “en route” to the passive placement goal. Thus even in the
absence of the door, some directional information derived from entering the room may
influence behavior following passive placement on the goal. This suggestion is consistent
with a recent finding showing that rats use the point of entry into a curtained enclosure
surrounding the water maze to navigate despite the presence of a stable array of distal
curtain cues (Hynes, Martin, Harley, Huxter, & Evans, 2000). In Experiment 2 of the
present study, the stable array of cues was present in the room and animals entered through
a curtain that blocked the south wall but did not surround the maze. Thus, entrance into
the space immediately surrounding the water maze may influence navigational behavior
through a map or direction setting/resetting mechanism.
If it were assumed that changing rooms (and, consequently, the majority of distal cues)
would require animals to form a new cognitive map of the environment, then the goal
location in the second environment may be considered arbitrary. The present findings
suggest that this may not be the case. If the platform location in room B was in the center
of the SW quadrant (i.e., the same as in room A relative to the door/entrance) then the
paths to the goal would have been relatively shorter and possibly more direct. For example,
all rats in the first experiment crossed the former goal location in the SW quadrant before
escaping to the platform in the NW quadrant. Consequently, if we had used the SW
quadrant as the goal, it may have been reasonable to conclude that rats can form a new
cognitive map based solely on a single passive exposure to the environment, what has
been termed instantaneous transfer (Morris, 1981; Keith & McVety, 1989) or perceptual
vector deduction (Alyan, 1994). It is not known whether this scenario has occurred in
past studies; however, our results suggest that there are other influences from polarizing
cues associated with the door/entrance.
The fact that individual differences in place acquisition were unrelated (nonparametric
analysis), or even negatively related (parametric analysis), to latent learning performance
following passive placement in the first experiment, but were positively correlated in the
second experiment suggests that the presence or absence of a common polarizing cue
may influence which underlying learning mechanisms are expressed. Other studies have
revealed individual differences in place versus cue learning. For example, using a concur-
rent cue/place task (Sutherland & Rudy, 1988), McDonald and White (1994) demonstrated
that individual differences in place versus cue responding on a posttraining competition
test were predicted by earlier performance during place acquisition. Poor place learners
with long escape latencies during acquisition swam to the visible (cued) platform at a
new location in the pool on the competition test, whereas good place learners with shorter
latencies swam to the “old” spatial location relative to extramaze distal cues. Thus, poor
place learners may be predisposed to respond to single, salient cues rather than to spatial
relational information. Lesion results of their study indicated that damage to the hippocam-
pal system lead to a cue bias on the competition test and poor place learning, whereas
damage to the dorsolateral striatum resulted in a place bias on the competition test and
good place learning. Response biases in the present study may represent subtle individual
differences in the degree of control exerted by one or the other of these two cerebral
procedures and the specific neurobiological substrates that may contribute to water maze
DEVAN ET AL.
performance when a pretraining design is employed. In addition to the effects of salient
or polarizing cues demonstrated in the present study, there may be other problems with
pretraining procedures. Pretraining procedures are often used to familiarize animals with
the procedural aspects of the water maze task, with the assumption commonly being made
that subsequent training in a new environment should be more sensitive to cognitive-
spatial mapping processes. If so, then manipulations designed to interfere specifically
with “cognitive” learning and memory processes should selectively impair performance
after pretraining. However, several studies demonstrate that when animals are pretrained in
the water maze, the effects of systemic and intrahippocampal administration of cholinergic
in a novel environment (see Cain, 1998; Moser & Moser, 2000, for reviews). Similarly,
it was shown recently that saturation of hippocampal LTP does not impair place navigation
following pretraining (Otnæss, Brun, Moser, & Moser, 1999), although it does disrupt
acquisition without pretraining (Moser, Krobert, Moser, & Morris, 1998; Moser & Moser,
1999). Therefore, it is possible that hippocampal LTP may not be necessary for relearning
a place response in a different room if a simple recalibration of an inertial compass (i.e.,
path integration) is sufficient to solve the problem (Barnes, 1995).
The effects of pretraining are further complicated by disagreement about whether the
specific contribution of the hippocampus to spatial navigation is via map-based learning or
via path integration (McDonald & Hong, 2000; Alyan & McNaughton, 2000; Maaswinkel,
Jarrard, & Whishaw, 2000; O’Keefe & Nadel, 1978; Pearce, Roberts, & Good, 1998).
Moreover, animal studies using radial arm and water mazes (Devan, Goad, & Petri, 1996;
McDonald & White, 1995), as well as human studies using functional neuroimaging
(Maguire, Burgess, Donnett, Frackowiak, Frith, & O’Keefe, 1998; Maguire, Burgess, &
O’Keefe, 1999), suggest that the hippocampus is not the only structure that contributes
to spatial navigation. These studies support the proposed involvement of several brain
regions, including the caudate nucleus, in a spatial navigation network. In the water maze,
the strength and persistence of spatial behavior is influenced by specific reinforcement
contingencies (Devan & McDonald, 2001; Devan, Stouffer, Petri, McDonald, & Olds,
2001) that may involve the function of extrahippocampal circuits, such as a habit-based
corticostriatal system (Devan, McDonald, & White, 1999; Devan & White, 1999; McDon-
ald & White, 1993; Mishkin, Malamut, & Bachevalier, 1984; Mishkin & Petri, 1984;
Petri & Mishkin, 1994), which has been shown to mediate spatial performance guided
by salient cues late in training (Packard & McGaugh, 1996).
In conclusion, the present results suggest that the variability in findings among previous
latent learning studies using a two-room procedural pretraining design in the water maze
may be a function of individual differences in the stimulus control of behavior under
specific experimental conditions (e.g., the presence or absence of common “polarizing”
cues and the exact relationship between initial start and goal positions). We suggest that
careful consideration should be given to such experimental variables in neurobiological
investigations employing pretraining procedures.
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