| |
Introduction
The Object Recognition (OR), Novelty Response or Novelty Scan Test is an important experiment to investigate the effects of drugs or knock outs on novelty response and memory.
Therefore we developed a plug-in that applies special OR-algorithms to the three locomotion tracks our tracking software Viewer records for each animal (body point track, nose tip track, tail track).
Recognition events are described by six parameters with user-defined thresholds.
On top the plug-in provides an object database where all your objects are described and where the relative attractivity of each object can be computed from the data you acquired so far.
Parameters to detect object recognition events
To differentiate an animal's real interest in an object from just crossing the object, different parameters are important.
First of all you have to know, which part of the animal is close to the object. Real object interest takes place, if an animal is close to an object with its nose. Thus it is essential that our tracking software not only detects the animal's position in the arena, but also its posteroanterior alignment.
In addition to the distance between object and nose, we examine whether the object is within the animal's visual angle or not. The animal's locomotion speed and the time the animal spends within the defined maximum distance are further parameters the plug-in considers.
To make the data even more significant, you can determine whether or not object recognition events have to go along with sniffing behavior (head stretches).
|
 |
 |
Configuration of the Object Recognition Plug-In
User-definable parameters
To detect object recognition behavior in the way you want to, you can implement your own definition of each parameter.
To find settings that deliver your desired outcome, it is possible to apply changed parameter thresholds to a recorded track
again and again.
User definable parameters are:
• Minimum distance to object
• Width of the animal's visual angle
• Maximum velocity within the minimum distance
• Minimum duration of stay within the minimum distance
• Maximum duration at the object
• Sniffing behavior (head stretches)
You can decide how to use the parameters: All, only one or a combination of some.
|
|
 |
|
|
|
| Data Analysis
Single experiments and groups
Multiple experiment results can be pooled for a combined analysis. The table in the upper right corner contains one row for each experiment in a data pool. This pool is saved in a group file. The left table contains all object interest events of the experiment selected in the right table, whereas the table in the middle contains statistics for all experiments listed above. The tables provide the following data:
• Time of an inspection
• Duration of an inspection
• Which object has been inspected
• Latency to first visit
• Number of visits
• Percentage of visits
• Duration of the visits
• Percentage of the duration
In the display area in the lower part you can select diagrams for all different kinds of parameters calculated in the tables from a dop-down-menu.
|
|
 |
The bubble time chart provides an impressive overview of all object inspection events. The size of the bubble represents the time all user definable parameters (object within angle of view, animal within max. distance to the object, animal within max. velocity within max. distance, min. time spent within max. distance, sniffing behavior (head stretches)) where redeemed for each inspection event.
|
|
|
Inter group analysis
In addition to single experiment analysis and group statistics, the plug-in offers the possibility to compare group results, too. You can even move single experiments from one group to another in a comfortable way.
The figure on the right shows data for three different groups (interest in two objects).
All data and graphs can be exported in various formats.
|
|
 |
|
|
|
| The Attraction Factor
The Attraction Factor is a factor for each single object that is used in the experiments. It is a parameter that classifies the interest of animals in this single object without a second object being present.
Before starting with the object recognition experiments, the Attraction Factor is measured for each object you want to use.
How is the Attraction Factor measured?
Basically you do a novelty response experiment with this single object. The data of these experiments is stored in reference files.
How is the Attraction Factor used?
When you did the object recognition experiments you can use the reference files to normalize your experiments.
With this procedure it is possible to normalize all experiments by eliminating the difference in the individual object's attraction.
|
|
|
|
|
|
If you have questions concerning this product, please don't hesitate to use the following e-mail address:
viewer@biobserve.com |
|
|
|
