Abstract: Large-scale rodent behavioral experiments with complicated testing procedures conducted over several years (e.g. genetic mapping of operant drug taking) need rigorous control on the quality of the data. This webinar will discuss methods used in my lab where we generate ready to use MedPC macros from a spreadsheet for new test sessions, cell phone notification on the completion of behavioral tests, nightly automated data assembly, daily notification of procedural changes for individual animals. Potential errors are checked automatically at several points with messages sent to the users. This system is put together using a relational database (sqlite), several ad hoc computer programs (perl, python, or shell), a cloud storage service (Dropbox), and a messaging system (slack). By turning much of the experiment planning and error checking procedure into computer code, we improve experimental efficiency and data quality.

Presented by:

Hao Chen, PhD
Associate Professor
Department of Pharmacology, Addiction Science, and Toxicology
University of Tennessee Health Science Center

Lecture Materials