EthoVision XT - The Morris Water Maze Test
Last updated: Jul 25, 2026
The Morris Water Maze Test
Introduction
the morris water maze test
The Morris water maze is a behavioral procedure designed to test spatial memory. It was developed by neuroscientist Richard G. Morris in 1984, and since its initial description it has become a very popular paradigm for the study of learning and memory in rodents (D'Hooge and De Deyn, 2001). In the water maze paradigm, a rat or mouse is placed into a small circular pool of water which contains a hidden platform (the Atlantis platform). The platform is either fixed (a few millimeters below the water surface) or adjustable. In the latter case, the platform is submerged at the start of the trial (about 15 centimeters, depending on the device) and remains submerged until the subject finds the location of the platform. The platform is then automatically raised. Visual cues, such as colored shapes, are placed around the pool to aid the animal in learning to locate the platform. After sufficient training, a capable rat can swim directly from any release point to the platform. Next, animals are treated and the effects on spatial learning and memory are evaluated based on how they now perform in the Morris water maze. Figure 3.1 A rat in a Morris water maze.
the sample experiment
EthoVision XT comes with a sample experiment that shows you how a Morris water maze test is carried out with EthoVision XT. It includes a number of videos from a true research project and shows interesting patterns of spatial behavior depending on the age of the subject. If the sample experiment was installed during installation of
EthoVision XT, you can open it directly: Choose File > Restore
*Backup and browse to C:\Users\Public\Documents\Noldus*
EthoVision XT\Experiments\Sample Experiments. Select the file with extension EVZ and click Open. If you do not find the sample experiment, download it from
MyNoldus.com. First log in or register, then choose Downloads >
EthoVision XT > Sample Experiments.
references
D'Hooge, R. and De Deyn, P.P. (2001). Applications of the Morris water
maze in the study of learning and memory. Brain Research Reviews, 36,
performance in the Morris water maze. Behavioral Neuroscience, 107,
EthoVision XT and the Morris water maze test
For the complete list of publications, see the results in Google Scholar.
Physical setup
The following suggestions are meant to optimize video tracking: The camera should have a good view of the entire region the animal can be in. The arena should fill the field of view. There must be maximum contrast between the background and the animal. If you use dark rats in the water maze, you can color the water with milk powder (400 g, pre-dissolved in 2 l). It is also possible to track white rats or mice with dark coloring in the water: add 300 g of tempera black nontoxic powdered paint to a 45-l pool. If you have reflections in your image, EthoVision XT may confuse those reflections with your subject, and track the reflections rather than your animal. Place four (or more) bulbs round the pool, below the level of the water surface or other indirect lighting above the water maze (see Figure 2). 'Globe' type bulbs are ideal (twice the diameter as standard incandescent light bulbs). They should be close enough to the pool wall so that there is no direct line of sight between the bulbs and the camera lens. The light is reflected off the walls and ceiling, so that it only reaches both the lens and water surface indirectly. The water temperature should be ± 26 °C, which is cold enough to encourage the animals to seek the platform, but not too cold to induce hypothermia.
Figure 3.2 Lighting a water maze. Left: view from
side, right: view from above.
The Morris water maze test in EthoVision XT
Create an experiment. For details, see Chapter 1 of this manual, or in
EthoVision XT press F1 and see Setup an Experiment in the EthoVision
XT Help.
arena settings
Choose Setup > Arena Settings > ...
We assume that you followed the procedure in arena settings on page
15. The zone groups in your experiment depend on what zone template you chose when creating the experiment.
Platform, quadrants - This zone template creates one arena
settings profile with a zone group Platform with zones Platform and Platform Zone (the zone around the platform) and a zone group Quadrant with a zone for each quadrant.
Platform, quadrants, corridors, border - This zone template creates
four arena settings profiles, one for each quadrant. The South-West Platform profile, for example, contains a zone group Platform with zones Platform and Platform Zone (the zone around the platform), a zone group Quadrant with a zone for each quadrant, a zone group Thigmotaxis with zone Border Zone, and a Whishaw's corridor for the other quadrants than the one with the platform. Whishaw's corridor is an 18-centimeter wide path from the starting location to the platform. This corridor is designated as the correct route and if a rat deviates from this route at any point it receives a maximum of one error on that trial (Whishaw's error). To be able to determine whether the animal deviates from this route, you should define the rest of the arena as an Outside corridor zone. A Whishaw's corridor is defined for each release point you use. By creating separate Arena Settings for each corridor, you can select the appropriate Arena Settings for data acquisition depending on the release point for that trial. To resize and reshape a zone, click first the Point edit mode button on
the toolbar, then move the corners of the zone outline. Hold Shift down
to keep the same aspect ratio of the shape. Hold Ctrl to enlarge/reduce
the shape size in all directions.
Figure 3.3 Part of the South-West Platform arena settings profile. The zones
in the zone groups Platform and Whishaw's Corridor NW are displayed.
Zone for analyzing thigmotaxis
To quantify thigmotaxis, that is, persistent swim along the wall of the pool, create an additional zone group, and draw a circle which should be the internal margin of the zone. Place the zone label between this circle and the outline of the arena.
trial control settings
In the Trial Control Settings you can define conditions for the start and stop of the track.
Choose Setup > Trial Control Settings > Open one of the following:
Default (no max duration). When you use this profile, tracking
stops when you click the Stop trial button.
Max Track duration 1 min - When you use this profile, tracking
starts automatically 2 seconds after the animal has been placed in the maze. The track stops automatically when the center-point of the animal has been in the zone Platform for at least 5 seconds, or when 60 seconds have elapsed since the start of the track.
Max Track duration 2 min - When you use this profile, tracking
stops when the center-point of the animal has been in the zone Platform for at least 5 seconds, or after 2 minutes if the animal does not find the platform within that time.
Using an adjustable platform
If you use an adjustable platform you can define an action to raise the platform when the animal swims around the platform. Note that you need the Trial & Hardware Control module to be able to control the platform.
detection settings
Choose Setup > Detection Settings > Detection Settings 1.
We assume that you followed the procedure in detection settings on
page 17.
Check in the Video Section that the sample rate is set to 5 samples/
second (for rats) or 12.5 samples/second (for mice).
Advanced detection settings
If detection of the subject is not optimal after using the Automated setup function (page 17), do the following: 1. Check that either Dynamic subtraction or Differencing is selected as
the detection method. Differencing is the preferred option if you
work with hooded animals. 2. When using Dynamic subtraction - Move the slider to define the animal's contrast. The animal must be fully detected in all parts of
the arena and the noise must be minimal. Specify the Current frame
weight. A low value (for instance, 10-20) usually works well.
When using Differencing - Set the Sensitivity slider. The slider
determines what difference in contrast from the background is seen as the animal.
For more information, see Configure Detection Settings in the
EthoVision XT Help.
trial list
Choose Setup > Trial List.
Defining Independent Variables
Enter your independent variables such as: Subject ID with the ID of your animals as predefined values. Phase with Training and Probe as predefined values. Treatment with Treated and Control as predefined values. Dose with numerical values (e.g. 0.1 mg/kg, 0.5 mg/kg, etc.) Day after treatment (with values 1, 2, etc.) Name of the experimenter, etc.
Making a list of trials
If you want, you can pre-define all your trials here. Click the Add Trials
Acquiring data
protocol
In a typical water maze test, an animal is put in the maze at a predefined position at the rim of the pool, facing the wall. Lower the animal gently into the water (e.g. in a paper cup), avoiding stress as much as possible. Before you start data acquisition, make sure the appropriate arena settings profile, depending on the starting location of the animal, is selected in the Acquisition Settings window.
Training trials
In training trials, the animal starts swimming and the trial stops when the animal has found the platform or when the maximum trial duration has been reached.
Probe trials
After the training trials, a probe trial is conducted in which the escape platform is removed from the pool and the animal allowed to swim for 60 sec. Thus typically each animal is tested n times (training) + 1 time (probe). Each test corresponds to a trial in EthoVision XT.
Reversal training trials
In reversal learning tasks, after one location has been thoroughly trained, the platform is moved to a different quadrant of the pool. Because it is hidden, it is not apparent that anything has changed until the animal fails to find the platform in its usual place. The focus is on how the animal reacts to this change and how quickly it learns the new location. In EthoVision XT, mark different types of trials with an independent variable in the Trial List. For example Type, with values Training and Probe. Or, a variable Platform Position with values SouthWest, NorthWest, etc. See also acquiring tracks on page 21.
Data Analysis
data preparation
Track smoothing
Choose Acquisition > Track Smoothing Profile. Select Lowess smoothing to remove the effect of body wobble. When the animal sits still on the platform, yet the body center- point still moves slightly due to system noise. This results in an overestimation of, for example, the total distance moved. Select
Minimal distance moved to only measure the total distance moved
over the time periods in which the animal was really swimming.
analysis profiles
Choose Analysis > Analysis Profile. The template experiment contains five analysis profiles:
Latency to reach platform - This profile contains the variable
Latency to platform to calculate how long it takes the animal to
find the platform. You can use the variable Distance to zone to
calculate Gallagher's index (Gallagher et al., 1993). The variable In quadrants calculates the frequency and duration of visits to each quadrant.
Path shape - The path shape can be determined by using the
variables Turn angle, Angular velocity and Meander.
Whishaws Corridor (only present if you chose a zone template with
corridors when creating the experiment) - In this profile, the
variable Inside Whishaw's Corridor calculates the time the animal
spent inside any of Whishaw's corridors. The variable Outside
Whishaw's Corridor calculates the time the animal spent outside
any of Whishaw's corridors.
Distance & Time - In this profile, the total Distance Moved and the
mean Velocity and the group means with their standard errors are
calculated.
Heading - In this profile, the mean Heading to each of the
platforms is calculated.
swim patterns
Thigmotaxis (wall-hugging swim)
This is a persistent swim along the wall of the pool that could include sporadic swims toward the center of the pool. To quantify thigmotaxis, calculate the time spent in the Thigmotaxis zone defined as on page 54, relative to the total track duration.
Random search
This is swimming over the entire area of the pool in straight swims (zig- zag pattern), or in wide circular swims. Divide the pool into quadrants or even more, smaller zones, then count the number of times each zone was visited, the time in zones. If zone visits/time are uniformly distributed across zones, the search pattern could be said to be random or at least covering the whole pool.
Scanning
The search path is restricted to a limited, often central, area of the pool. Do the same as above, but now covering only the area/zones towards the center (see Figure 1C in the paper Janus C. 2004. Learning and Memory 11: 337-346). Relate this to the time in the external zones.
Chaining/serial visits
This is circular swimming (in anticlockwise or clockwise direction) at a fixed distance from the wall, in which the escape platform was located. To quantify chaining, draw a specific circular crown zone. Calculate the time spent in this zone versus the time in the rest of the arena, or calculate rotations occurring in that zone.
Focal search
This is searching in a restricted area of the pool, usually the target quadrant. The path is characterized by a directional, straight swim to a specific area followed by dense concentration of superimposed loops and turns there.
To detect rapid changes in direction, use the Multi condition dependent
variable to define your criterion, for example Absolute Meander > 10 degrees/cm. This marks the time when Meander is greater than the threshold value. You can precisely capture the instances when the subjects turns and heads back to the target zone. Combine Meander with a In zone
variable in a Free Interval, to select the time from when the rapid
change in direction occurs, to when the subject enters the target area. In the Arena Settings, define a zone around the platform or any other target point, and name it Focal zone. In the Analysis profile, define a
Free interval from Interval start "Meander: Absolute Meander > 10
degree/cm" to Interval stop "In zone: Center point is in Focal zone".
In the figure below, the peaks in the Meander variable mark the sudden
changes in direction. The color bars represent the Free interval marking
the time between the directional change and the zone visit.
Direct swim path
This is the direct swim path to the location containing the escape platform.
Define an In zone variable based on the Whishaw's corridor (page 59)
to calculate the time spent in and outside this corridor before reaching the platform. See also the EthoVision XT Help.
Floating
A state of inactivity without forward movement. The plotted path is short, often with thick or tight sections caused by non-directional drift.
Quantify floating with Movement (Not moving) or a Multi condition
that includes Movement (Not moving) and In zone (Center point is not
near the wall of the pool; define a dedicated zone if necessary).
gallagher's proximity score
Cumulative search error (for training trials)
Gallagher et al. (1993; see page 50) proposed the Cumulative search error to provide information about the spatial distribution of the animal's search during training trials. This was obtained by sampling the position of the animal in the water maze (10 times per second), and calculating the averages of distance to the platform for 1-second periods (see Figure 6 in the original paper). The averages are then summed up. In EthoVision XT, you have two options: Calculate the Total distance from the platform.
In the Analysis profile, choose the dependent variable Distance to
zone, with the Statistic Total. This equals the "true" Gallagher's
Cumulative search error when sample rate = 10 samples/s. In most cases the Total distance from the platform highly correlates with the "true" search error. Calculate the "true" Gallagher's Cumulative search error. In the Data profile, select time bins (1 second).
b In the Analysis profile, define the dependent variable Distance to
zone, with the Statistic Mean.
Choose Analysis > Results > Statistics and Charts, click Calculate,
then export the results (Analysis > Export > Statistics).
d In Excel, open the export file and sum up the average values per
trial.
Average search error (for probe trials)
According to Gallagher et al. (1993), the Average search error is obtained by calculating the average distance of the animal to the platform location over 1-second intervals, and then averaging the values (Average proximity; see Figure 9 in the original paper). In EthoVision XT:
In the Analysis profile, choose the dependent variable Distance to zone,
with the Statistic Mean. This equals the Gallagher's Average search
error in all cases.
Data correction
For both probe trials and training trials, Gallagher et al. (1993) made a correction so that trial performance was relatively unbiased by differences in distance to the goal from the various start locations at the perimeter of the pool (see page 621 in the paper). If you want to apply this correction to your data: 1. Measure the distance D between the release point and the platform. In the EthoVision XT Trial List, define an independent variable D and for each trial enter the appropriate value depending on the release point used in that trial. Values will be used later in the Excel export file. 2. In the Analysis profile, define the dependent variables Distance to zone, In zone (not in platform) and Velocity. 3. Choose Analysis > Export > Raw Data. and choose Excel as File type. 4. In Excel, create macros/formulas that calculate (see the next page): - The average velocity v when In zone =1. - The time needed to reach the platform from that starting point: t= D/v. - Insert a new column Valid time, assign the value 1 if Recording time in the same line is higher than t. - Calculate the average distance to zone (platform) for when In zone =1 and Valid time =1 (use the Excel function averageifs). - Calculate the total distance to platform when In zone =1 and Valid time =1 (use the Excel function sumifs).
Figure 3.5 Example of Excel file for calculating corrected Total distance (see
text).
Source: EthoVision XT 17.5 Application Manual, The Morris Water Maze Test