In a standard PhenoTyper experiment animals are followed for six days, to distinguish novelty from baseline behavior, since habituation to the cage requires several days (Visser et al. 2006). Our test protocols take into account that several motivational systems are activated simultaneously or in succession. We consider this not a more complex test situation, but rather a more ecologically or biologically valid test condition.

The animal’s position and behavior are measured continuously, multiple times per second, 24 hours/day, during multiple days. The software computes a large number of parameters, including entries and time spent in specific zones, distance moved, velocity, track shape, and a number of specific parameters for specific tasks within the experiment. Data are summarized over time bins and spatial zones, resulting in  numerous end points for each animal. Even a relatively simple experiment will result in large data sets, allowing the detection of novel effects or side-effects of treatments. The software incorporates advanced algorithms for the analysis of high-content behavioral data, a prerequisite for high-resolution phenotypic discrimination in the massive data streams resulting from automated longitudinal observations.

Behavior is a sequential series of events. Its meaning resides in the programming of this sequential order. Since we capture the continuous flow of behavioral elements in relation to time, the sequential ordering can be described in numerical and graphical ways (transition matrices, pathway diagrams) and repetitive patterns of similar events with structured time intervals can be revealed. Data can be analyzed with our special software tools for lag sequential and t-pattern analysis.

As behavior is the result of complex interactions between various motivational systems and physiological states (e.g. arousal), it cannot be easily studied in separate narrowly focused tests without losing the interaction effects. Using our approach, it becomes possible to conclude whether a behavioral change is, for instance, due to a differential and combined contribution of exploration, anxiety, cognition or an altered circadian rhythm.

Click on the links below for more information about studies on: 

Automated Learning Tasks 

Anxiety

Chronic Pain 

Parkinson's Disease  

Visser, L. de; Bos van den, R.; Kuurman, W.W.; Kas, M.J.H.; Spruijt, B.M. (2006). Novel approach to the behavioural characteristics of inbred mice: automated home cage observations. Genes, Brain and Behavior, 5, 458-466.