High-Throughput Automated Olfactory Phenotyping of Group-Housed Mice - Reinert, Janine K.; Schaefer, Andreas T.; Kuner, Thomas (Frontiers in Behavioral Neuroscience, 2019)
Behavioral phenotyping of mice is often compromised by manual interventions of the experimenter and limited throughput. Here, we describe a fully automated behavior setup that allows for quantitative analysis of mouse olfaction with minimized experimenter involvement. Mice are group-housed and tagged with unique RFID chips. They can freely initiate trials and are automatically trained on a go/no-go task, learning to distinguish a rewarded from an unrewarded odor. Further, odor discrimination tasks and detailed training aspects can be set for each animal individually for automated execution without direct experimenter intervention. The procedure described here, from initial RFID implantation to discrimination of complex odor mixtures at high accuracy, can be completed within <2 months with cohorts of up to 25 male mice. Apart from the presentation of monomolecular odors, the setup can generate arbitrary mixtures and dilutions from any set of odors to create complex stimuli, enabling demanding behavioral analyses at high-throughput.