Knowledge Base

The Novel Object Recognition Test

Introduction

the novel object recognition test

The Novel Object Recognition (NOR) test was first described by Ennaceur and Delacour (1988). Rats or mice are exposed first to two identical objects and then one of the objects is replaced by a new (novel) object. The time spent exploring each of the objects is measured. The test has become popular for assessing visual memory in rodents in general and to test the effects of amnesic drugs in particular. The test is based on spontaneous behavior with no reinforcement such as food or shock. Non-amnesic animals will spend more time exploring the novel object than the familiar one. An absence of any difference in exploration time can be interpreted as a memory defect or, in case an amnesic drug is tested, a non-effective drug. This chapter describes how a NOR test can be conducted with EthoVision XT. On the downloads section of the Noldus website my.noldus.com, you find a number of sample experiments, including one that features a NOR test. Figure 4.1 A mouse exploring novel objects.

the sample experiment

To see how a Novel Object Recognition test is carried out in EthoVision

XT, see also the sample experiment Novel Object Recognition test

XT175 on the downloads section of the Noldus website

(my.noldus.com). Download this file and save it on your computer. In

EthoVision XT, choose File > Restore Backup and select the file. For

more information, see the document Description of sample

experiments of EthoVision XT.pdf.

references

Ennaceur, A.; Delacour, J. (1988) A new one-trial test for neurobiological studies of memory in rats, 1: Behavioral data. Behavioral Brain Research, 31, 47-59.

EthoVision XT and the novel object test

Benice, T.J.; Raber, J. (2008). Object recognition analysis in mice using

nose-point digital video tracking. Journal of Neuroscience Methods, 168,

Physical setup

The following suggestions are specifically to optimize video tracking:

For general information, see the section Physical setup in the

chapter The Open Field test on page 28. The objects should contrast with the animal. If necessary use a different setup for light and dark colored animals. Make sure that the objects do not move due to the activity of the animal. Either make sure the sides of the box are not reflective (for example, sand the box to make it matte), or exclude the sides from the arena. If your objects are close to the sides, you will need to track the animal when it is against the side.

The NOR test in EthoVision XT

Create an experiment from a template (Ctrl+T). Choose Open field

(round or square) as Arena template, and Novel object zones as Zone

template.

For details, see Chapter 1 of this manual, or in EthoVision XT press F1

and see Setup an Experiment in the EthoVision XT Help.

experiment settings

Choose Setup > Experiment Settings.

Under Video Source, and Tracked Features, make sure that the options

selected corresponds to your needs. If you want to use Deep learning technique to track the subject's nose,

under Body point detection technique choose Deep learning. Note that

in order to use this technique there are additional requirements. The PC must have a powerful graphics card which supports additional

software (CUDA). See Deep learning: Requirements and Limitations in

the EthoVision XT Help.

manual scoring settings

These settings enable you to record behaviors manually, using keystrokes. This is handy for example to record exploratory behaviors like sniffing. Choose Setup > Manual Scoring Settings. If you created the experiment from the template with novel object zones, the Manual Scoring Settings already includes one behavior,

Sniffing object. This is defined as "start-stop", which means that you

press a key (default: q) to score the start of sniffing, and then you press the same key once again to score the end of sniffing.

For more information, see Manual Scoring Settings in the EthoVision

XT Help.

note With the Rat or Mouse Behavior Recognition add-on, you can

have EthoVision XT detect sniffing and other behaviors, without the need to score them manually.

arena settings

Choose Setup > Arena Settings > Open Arena Settings 1. To set up your Arena Settings: 1. Click the Grab Background Image button to grab an image of the empty enclosure from the camera image. 2. Click 1. Draw Scale to calibrate and calibrate your arena (for details, see the EthoVision XT Help).

tip Draw the double-arrow in such a way it points to two opposite

walls of the open field, at the level where the animal moves (thus not at the top of the walls!). When done, enter the distance in real world units between the tips of the arrow. 3. Click 2. Select Shape and Draw Arena. Check that the arena covers the whole area in which you want to track the animal. Remember to include enough of the walls so that the animal is still tracked when it rears, but exclude any bright reflective rims that might interfere with tracking. Make sure the label stays inside the arena.

tip If the arena is not yet defined, and you want to divide it in equal

zones, click 2. Select Shape and Draw Arena. Choose the tool that

applies depending on the shape of your open field and draw the outline of the arena. 4. If you used the Zone template Novel object zones, click 3. Select Shape and Draw Zones.

Click the layer Zone group Objects. Check that the 'object 1' zone

and 'object 1 boundary' zone cover the object (Figure 4.2). If the predefined zones do not have the correct shape, delete the zones and draw new ones. 5. If necessary, draw additional zone groups/zones.

Additional zones

Zone group Floor and Wall. Check that the 'Floor' zone covers the

whole floor area of the open field (see Figure 4.3). Figure 4.2 Zones of the zone group "Objects".

Zone group Halves. Check that the 'West' and 'East' zones divide

the 'Floor' zone in two equal halves. Make sure that the vertical line crosses the entire 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. The template contains the

following profiles:

Default. When you use this profile, tracking starts automatically

two seconds after the animal has been placed in the arena. Tracking stops when you click the Stop trial button.

Track duration 10 min. When you use this profile, tracking starts

automatically two seconds after the animal has been placed in the arena. Tracking stops automatically after 10 minutes.

To sop tracking when exploration exceed a specified time

You can also stop tracking when the subject has spent some time around an object. For example, when the protocol specifies that in pre- test trials the animal must explore an object for at least 30 seconds. Figure 4.3 Open field with 'Floor' zone and 'Wall' zone.

Make a new Trial Control Settings, and immediately before the Stop

track box, insert a Condition box based on the variable In zone, or

another variable, or a combination of variables using Multi condition.

In the Condition settings, specify that Cumulative duration in the

boundary zone for that object must be greater than N seconds, for the nose point. If you use Multi condition, you can define "exploration" as a combination of variables. For example: In Zone for the noise point in the "object zone" is true + Head directed to Zone "object" is true + Velocity lower than 5 cm/s is true. The trial stops only when the cumulative time that the three criteria are met reaches the specified value.

To stop tracking automatically when no exploration occurs

To stop tracking automatically even when the animal does not explore the object, add another condition in parallel with the first one, which specifies to stop tracking after some time (e.g. 10 minutes), and combine the two conditions with an Operator box of type "ANY".

detection settings

Choose Setup > Detection Settings > Detection Settings 1.

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 the sample rate is set to at least 25 samples/second when tracking the nose and tail. 2. Check that either Dynamic subtraction or Differencing is selected as the detection method. Differencing is the preferred option if you work with hooded animals. 3. 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, 1 to 10) usually works well. A novel

When using Differencing, set the Sensitivity slider. The slider

determines what difference in contrast from the background is seen as the animal. 4. When detection still is not satisfactory, select Rodents / For occlusions as the tracking method and repeat step 2 above.

note If you want to use Deep learning technique to track the

subject's nose, note that there are additional requirements and limitations. Among other things, you need a powerful graphics

card. See Deep learning: Requirements and Limitations 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 Acclimation, T1, T2 as predefined values, where: - Acclimation to mark trials where the animal is free to explore the arena, with no objects present. - T1 to mark trials where the animal is presented with a pair of identical objects. - T2 to mark trials where one of the familiar objects is changed for another new (novel object test). Treatment with Treated and Control as predefined values. If you want, you can predefine all your trials here, or you can enter the independent variable values as you carry out the trials. You can also prepare the trials in Excel, randomize them and then paste the values into your Trial List. Furthermore, you can define a list of trials for batch acquisition. See Batch Data Acquisition in the EthoVision XT Help. Figure 4.4 An example of the Trial List with four planned trials.

Acquiring data

protocol

A typical NOR test consists of three phases:

Acclimation. The animal is placed in an empty arena for 10 minutes

to habituate to the environment. Tracking in this phase is optional. After 10 minutes, the animal is taken out of the arena and is put back in its home cage.

T1. After 15 minutes in the home cage, the animal is put back in the

arena in which two identical objects have been placed. The animal is put at a position midway between the objects and such that its nose points towards the wall. The animal is tracked for 3 minutes and is then taken out of the arena and put back in its home cage. Define a Trial Control Settings profile for this phase, then assign this profile to the trials of type T1.

T2. One of the objects in the open field is replaced with a novel

object (sometimes the other object is also replaced with an identical one) and the animal is put in the arena again. Tracking is done for 3 minutes. Define a Trial Control Settings profile for this phase, then assign this profile to the trials of type T2. See also acquiring tracks on page 21.

score behaviors manually

To score sniffing and other behaviors defined under Manual Scoring Settings, open the Manual Scoring tab on the Acquisition screen. There you find the key codes and the buttons for the behaviors. To score an instance of the behavior or its end, either press the key or click the corresponding button on the screen.

Notes

important If you do tracking from video, make sure you de-select

DDS in the Playback Control window.

You can also score behaviors after tracking. See Acquire Data >

Score behaviors manually in the EthoVision XT Help.

Data Analysis

data preparation

Track editing

Choose Acquisition > Edit Tracks. You can fix tracking errors and swap back nose-points and tail-points that have been swapped in tracking. Normally you will not need to edit your data.

Track smoothing

Choose Acquisition > Track Smoothing Profile > open MDM Filter 2 mm.

In this profile, the Minimal Distance Moved filter is used (option set to

Direct, with a threshold of 2 mm). When the animal sits still, the body

points may still move slightly due to system noise. This results in an overestimation of, for example, the total distance moved. With the minimal distance moved filter, you measure the total distance moved over the time periods in which the animal was really walking. Adjust the threshold if necessary, based on your setup and sample rate.

Review video and behaviors

If you have scored behaviors manually, you can review the video and if

necessary edit the data. Choose Acquisition > Score behaviors

manually. For details, see Score behaviors manually in the EthoVision

XT Help.

selecting data

Choose Analysis > Data Profile.

You can select (Filter) your tracks according to your independent

variable values (for example, Treated animals only) and also select parts of tracks (Nesting). Figure 4.5 shows a data profile to compare 'Novel Object' and 'Familiar Object' trials which uses Filters. This way you create groups of tracks to obtain group statistics for each group.

analysis profiles

The template experiment contains four analysis profiles:

Touching objects. This analysis profile contains an In zone variable

Nose touching objects to calculate the frequency, duration, and latency of when the nose-point of the animal touches the objects.

The variable Distance to objects is used to calculate the mean and

standard error of the animal's nose-point to the objects. The Manually-scored behavior Sniffing object calculates the frequency and duration, with standard errors, of the instances when you scored Sniffing object during the trials.

In halves. In this analysis profile, the In zone variable In Halves is

used to calculate the frequency, duration and latency of when the center-point of the animal was in either half of the arena.

Figure 4.5 An example of data selection to compare two data sets in your

experiment.

Head directed to zone. This analysis profile contains two Head

directed to zone variables, one for the novel object and one for the

familiar object. For each object, the center plus a 0.10 cm radius is

used as the Point of interest. The frequency and duration for Head

direction to zone is calculated when the nose-point is in the zone of

the corresponding object.

Distance & Time. With the variables Distance Moved and Velocity,

the total distance moved and the mean velocity are calculated. All analysis profiles also contain settings to calculate the group mean and standard errors of the statistics for trial groups.

exploratory behavior

You can quantify exploratory behavior with the Analysis profiles described above, or you can create your own Analysis profiles. There is usually variation between subjects in the time spent exploring an object. To account for this variation, you can select the part of each track up to when the animal explored an object for a specific time, and then analyze the behavior of the subject in that part. To do so, use the Free Interval function in the Data profile. 1. Choose Analysis > Data Profile > New. 2. Under Nesting, click the button next to Free Interval. 3. Select the following: - As a Start criterion: Time (select Track start). - As a Stop criterion: Dependent variable. Select the variable In

zone, and the statistic Cumulative duration. In the settings,

specify which zone the animal explored, and with which body point (for example, Novel object, nose point). Set the total exploration time. 4. Click OK and insert the resulting box as in the figure below. 5. In the Analysis profile, choose the endpoints (distance moved, time spent in zones etc.). 6. Choose Analysis > Results > Statistics and Charts. The results are calculated for the time until exploration reaches the duration specified. For more examples, see Free interval in the EthoVision XT Help.

heatmaps

Heatmaps facilitate identification of "hotspots" and clustering of data

points. Choose Analysis > Results > Plot Heatmaps. Next, click Plot

Heatmaps on the toolbar.

Figure 4.6 A heatmap of a trial with two

objects, unfamiliar (left) and familiar (right).

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Source: EthoVision XT 17.5 Application Manual, The Novel Object Recognition Test