Knowledge Base

Introduction

The Radial Arm Maze Test

The radial arm maze was designed to measure spatial learning and memory in rats (Olton and Samuelson, 1976; Olton, 1978, 1985). The original apparatus consists of eight arms, each about 4 feet long, and all radiating from a small circular central platform. At the end of each arm there is a food site, the contents of which are not visible from the central platform.

The design ensures that, after checking for food at the end of each arm, the rat is always forced to return to the central platform before making another choice. For example, when investigating working memory, all arms are provided with a food reward and the animal should visit each arm only once.

Correct performance of the radial maze task requires intact spatial memory abilities. Performance is affected by hippocampal impairment and a variety of pharmacological agents (e.g., Janitzky et al. 2011).

References

• Janitzky, K, Schwegler, H., Kröber, A., Roskoden, T., Yanagawa, Y. & Linke, R. (2011). Species-relevant inescapable stress differently influences memory consolidation and retrieval of mice in a spatial radial arm maze. Behavioural Brain Research, 219(1), 142-148.
• Olton, D.S. (1978). Characteristics of spatial memory. In: Hulse S.H., Fowler H, Honig W.K. (Eds.), Cognitive processes in animal behavior, Hillsdale, NJ: Lawrence Erlbaum Associates, 341-373.
• Olton, D.S. (1985). The radial arm maze as a tool in behavioral pharmacology. Physiol. & Behav. 40, 793-797.
• Olton, D.S., & Samuelson, R.J. (1976). Remembrance of places passed: Spatial memory in rats. Journal of Experimental Psychology: Animal Behavior Processes, 2, 97-116.
• Wenk, G.L. (2004). Unit 8.5A Assessment of Spatial Memory Using the Radial Arm Maze and Morris Water Maze, in: Current Protocols in Neuroscience, John Wiley and Sons, Inc.

Physical Setup

The following suggestions are specifically 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 white animals in the maze, make sure the floors of the arms are dark and vice versa. Preferably, the floor of the room should be the same color (and matted) as the maze, contrasting with the animal.
• Lighting should be uniform and even with no shadows.
• If you have reflections in your image, EthoVision XT may confuse those reflections with your subject, and track the reflections rather than your animal. To prevent reflections, place indirect lighting above or around the maze. 'Globe' type bulbs twice the diameter as standard light bulbs are ideal. They should be close enough to the maze so that there is no direct line of sight between the bulbs and the camera lens. The light should reflect off the walls and ceiling, so that it only reaches both the lens and radial maze indirectly.

The Radial Arm Maze Test in EthoVision XT

In EthoVision XT, you can set up a radial 8-arm maze experiment by using a predefined template in the guided setup. Create an experiment. For details, see Chapter 1 of this manual, or see Setup an Experiment in the EthoVision XT Help.

Experiment Settings

1. Make sure that the radial maze is connected to the EthoVision XT computer. To connect the radial maze to EthoVision XT, you must have the Trial and Hardware Control add-on and the USB-IO box. The procedure and the necessary cabling may differ between manufacturers of the radial maze. Please see the accompanying documentation.
2. Choose Setup > Experiment Settings.
3. Under Video Source and Tracked Features, make sure that the options selected correspond to your needs. To adjust the camera settings, click the video icon in the camera row.
4. If you want to use the 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. Among other things, you need a powerful graphics card. See Deep learning: Requirements and Limitations in the EthoVision XT Help.
5. Under Trial Control Hardware, select Use of Trial Control Hardware and click Settings. Select Noldus USB-IO box.
6. In the Device Configuration window, for TTL ports 1 to 4, under Device type, select Custom Hardware. Next, type in Doors1&2 for TTL Port 1, Doors3&4 for TTL Port 2, Doors5&6 for TTL Port 3, and Doors7&8 for TTL Port 4.

Arena Settings

Choose Setup > Arena Settings > Open Arena Settings 1.

1. In the Grab Background Image window, click the Grab button to grab a background image of the radial maze from the camera image.
2. Click 1. Draw Scale to calibrate your arena. For details, see Make the arena in the EthoVision XT Help.
3. Click 2. Select Shape and Draw Arena and check that the predefined arena has the correct shape and size. If necessary, adjust the contour of the arena to fit the radial maze.
4. If you used the Zone template, click 3. Select Shape and Draw Zones. Check that the zones have the correct shape and size. If necessary, resize or add new zones.
5. If you are using automated doors, click Arena - Hardware mapping in the Arena Settings window to assign the doors to 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 starts automatically 2 seconds after the animal has been placed in the Center zone. Tracking stops manually (for example when you click the Stop trial button).
• Track duration 10 min - When you use this profile, tracking starts automatically 2 seconds after the animal has been placed in the Center zone. The track stops automatically when 10 minutes have elapsed since the start of the track.

Controlling Automated Doors

If you want to control the automated doors with EthoVision XT, you need to create new Trial Control Settings.

An example of Trial Control Settings for a protocol as described in Unit 8.5A of Current Protocols in Neuroscience (2004) to test basic working memory is the following:

• Start condition. We assume that the animal is released in the Center zone with all doors closed. Tracking starts 3 seconds after the animal is put in the Center zone.
• Opening all doors simultaneously. You can create a Sub-rule with a Reference for this. In the Sub-rule, each door is opened. For each door, you need to create a separate Hardware Action box, with the corresponding Device name (for example '1&2') and appropriate Action ('Output 1 High' which opens door 1). The Sub-rule 'open beginning' contains the sequence in which doors are opened. The Reference box to the Sub-rule is activated immediately after the Start trial command.
• Closing and then opening all doors. When the animal has visited the Goal zone of one of the arms and returns to the Center zone, all doors are closed and re-opened after 5 seconds. You can create a Sub-rule with a Reference for this. In the Sub-rule, you need to create a Zone transition Condition for each arm separately. Next, all eight Zone transition Conditions need to be connected to an Operator 'Any input True'. With a Hardware Action box, all 8 arms are then closed. Place the Hardware Action box for all doors in a sequence similar to opening doors as described in the opening step above.
• Stop condition. The trial stops when the animal has visited the Goal zones of all 8 arms OR after 15 minutes have elapsed since the start of tracking.
  • For the first criterion (the animal visits the Goal zone of all arms), use an In Zone Condition for each Goal zone. All eight In Zone Condition boxes are connected to the Operator 'Num simultaneously True inputs'.
  • For the second criterion (after 15 minutes), use a Time Condition box.
  • The two criteria must be combined with OR logic. The Time Condition box and the 'Num simultaneously True inputs' Operator box are connected to an 'Any input True' Operator box. An extra delay of 3 seconds can be included before the trial stops.

Detection Settings

Choose Setup > Detection Settings > Detection Settings 1.

Advanced Detection Settings

1. Under Video, check that the sample rate is set to 25 or 30 samples/second for multiple body-point tracking.
2. Click Advanced.
3. Under Method:
   • By default, Static subtraction is selected as the detection method and Rodents / Default as the method for nose-tail detection. The background in a radial maze test usually does not change much, so Static subtraction usually works well. Make sure the lighting is even and there are no shadows in the maze.
   • If after running some test trials you get nose-tail swaps, try using the tracking method Rodents / For occlusions.
   • If you selected to use the Deep learning technique to track the subject's nose, next to Deep learning click Define and select a box around the subject. Make sure that the box includes the subject's nose. For details, see the EthoVision XT Help.
4. Optional: Select Track noise reduction. Under Smoothing, set Track noise reduction to On. In some cases better quality tracking can be obtained by applying track noise reduction.

Source: EthoVision XT 19 - Application Manual