Measuring Behavior 2005: Symposia

SYMPOSIUM

The automation of observing and analyzing rodent behavior: possibilities and limitations

ORGANIZED BY:

Berry Spruijt

(Utrecht University, Utrecht, The Netherlands)

The increasing number of genetically modified animals to be characterized demands for the development of a reliable tool for observing and analyzing challenge-induced and baseline behavior. Since a functional interpretation of the gene effect on behavior is the ultimate goal of many phenotyping studies, an ethological rationale underlying testing is a logical consequence. So far batteries of already existing tests that have been applied involve two caveats:

Behavior is induced in a novel environment and, thus, the limited observation time excludes assessment of habituation, baseline levels, rhythmicity, etc.
Most tests have a specific focus on one motivational system, e.g. exploration, anxiety, etc., and a limited number of measurement parameters, whereas complex functions are the result of interacting motivational systems.

Recently, several systems have been developed equipped with hardware and software allowing observations over days. Since the animals are very precisely monitored by computers, behaviors have to be explicitly defined in terms of movement, position and form. Implementation, thus, requires redefining ethograms, which is an exciting process. Explicitly defining behavioral elements makes one aware of subjective influences in previously defined behaviors. The inevitable validation of data collected with new systems against data obtained with previously used well-known tasks can never be full proof as the latter tests have never been standardized themselves. Video imaging techniques also has disadvantages in that they do not cover neurological disturbances.

Apart from standardization and validation another issue emerges: the challenge resides not only in what can be measured, but how can large sets of data be reduced to a functional description of behavior and to what extent can relevant changes in complex behaviors of vast numbers of genetically modified animals be detected. For instance, the at first sight simple behavior "activity" consists of different components (speed, bouts, angularity, etc.) in combination with different spatial zones; modeling methods are required for an appropriate description and deduction of critical parameters, which then have to be subjected to statistical procedures such as principal component analysis and t-pattern analysis. In fact, a complex test requires complex statistics to have the full benefit of this approach. The fact that data can now be collected over days contributes significantly to the power of statistics.

Presently different systems are being developed these days and continuously extended in the near future with devices and sensors allowing the measurement of anxiety and conditioned place preference, conditioned place aversion, object recognition, etc. It is self-evident that the automated collection of data obtained in standardized and validated cages contributes to the reliability and reproducibility of such behavioral changes displayed by mutant mice. Different data sets illustrating and validating the applied techniques will be presented with a perspective on future: possibilities and limitations. In this symposium different systems which are being used will be highlighted: IntelliCage and PhenoLab. Secondly, attention will be paid to video imaging and the data streams generated by such an automated system and possibilities for analysis.

Speakers:

Berry Spruijt (Utrecht University, Utrecht, The Netherlands). Introduction.

Saskia Arndt (University of Cologne, Cologne, Germany). The "mouse fitness centre": A standardized test system to assess motor function.

Hans-Peter Lipp (University of Zürich, Irchel, Zurich, Switzerland). Automated behavioral analysis of mice using INTELLICAGE: inter-laboratory comparisons and validation with exploratory behavior and spatial learning.

Serge Belongie (University of California, San Diego, La Jolla, CA, U.S.A.). Monitoring animal behavior in the Smart Vivarium.

Leonie de Visser (Utrecht University, Utrecht, The Netherlands). Multi-level analysis of mouse behaviour in a home cage environment using PhenoLab.

Pim Kuurman (Utrecht University, Utrecht, The Netherlands). Behavioral phenotyping: Getting more information from video tracking data.

Alexander Cupido (Erasmus Medical Center, Rotterdam, The Netherlands). The Erasmus Ladder: a new tool for the automated measurement of motor performance and motor learning in mice.

Last updated: 19 October 2005