Gathering Self-Initiated Rat Behavioral Data to Characterize Post-Stroke Deficits

Behavioral testing in rat models is frequently utilized for diverse purposes, including psychological, biomedical, and behavioral research. Many traditional approaches involve individual, one-on-one testing sessions between a single researcher and each animal in an experiment. This setup can be very time consuming for the researcher, and their presence may impact the behavioral data in unwanted ways. Additionally, traditional caging for rat research imposes a lack of enrichment, exercise, and socialization that would normally be typical for the species, and this context may also skew the results of behavioral data. Overcoming these limitations may be worthwhile for several research applications, including the study of acquired brain injury. Here, an example method is presented for automatically training and testing individual rat behavior in a colony cage without the presence of humans. Radio frequency identification can be utilized to tailor sessions to the individual rat. The validation of this system occurred in the example context of measuring skilled forelimb motor performance before and after stroke. Traditional characteristics of post-stroke behavioral impairments and novel measures enabled by the system are measured, including success rate, various aspects of pull force, bout analysis, initiation rate and patterns, session duration, and circadian patterns. These variables can be collected automatically with few limitations; though the apparatus removes experimental control of exposure, timing and practice, the validation produced reasonable consistency in these variables from animal to animal.