title: Automated, quantitative cognitive/behavioral screening of mice: for genetics, pharmacology, animal cognition and undergraduate instruction.
abstract: We describe a high-throughput, high-volume, fully automated, live-in 24/7 behavioral testing system for assessing the effects of genetic and pharmacological manipulations on basic mechanisms of cognition and learning in mice. A standard polypropylene mouse housing tub is connected through an acrylic tube to a standard commercial mouse test box. The test box has 3 hoppers, 2 of which are connected to pellet feeders. All are internally illuminable with an LED and monitored for head entries by infrared (IR) beams. Mice live in the environment, which eliminates handling during screening. They obtain their food during two or more daily feeding periods by performing in operant (instrumental) and Pavlovian (classical) protocols, for which we have written protocol-control software and quasi-real-time data analysis and graphing software. The data analysis and graphing routines are written in a MATLAB-based language created to simplify greatly the analysis of large time-stamped behavioral and physiological event records and to preserve a full data trail from raw data through all intermediate analyses to the published graphs and statistics within a single data structure. The data-analysis code harvests the data several times a day and subjects it to statistical and graphical analyses, which are automatically stored in the "cloud" and on in-lab computers. Thus, the progress of individual mice is visualized and quantified daily. The data-analysis code talks to the protocol-control code, permitting the automated advance from protocol to protocol of individual subjects. The behavioral protocols implemented are matching, autoshaping, timed hopper-switching, risk assessment in timed hopper-switching, impulsivity measurement, and the circadian anticipation of food availability. Open-source protocol-control and data-analysis code makes the addition of new protocols simple. Eight test environments fit in a 48 in x 24 in x 78 in cabinet; two such cabinets (16 environments) may be controlled by one computer.
authors.affiliation: Department of Psychology, Rutgers University; galliste@ruccs.rutgers.edu.
authors.forename: C R
authors.initials: CR
authors.lastname: Gallistel
authors.affiliation: Department of Psychology, Rutgers University; Department of Psychology, Koç University.
authors.forename: Fuat
authors.initials: F
authors.lastname: Balci
authors.affiliation: Department of Psychology, Rutgers University; Center for Neural Science, New York University.
authors.forename: David
authors.initials: D
authors.lastname: Freestone
authors.affiliation: Department of Psychology, Rutgers University.
authors.forename: Aaron
authors.initials: A
authors.lastname: Kheifets
authors.affiliation: Department of Mathematics & Computer Science, Fairfield University.
authors.forename: Adam
authors.initials: A
authors.lastname: King
mesh_terms: D000818:Animals; D001522:Behavior, Animal; D003071:Cognition; D003214:Conditioning, Classical; D003216:Conditioning, Operant; D005824:Genetics, Behavioral; D057166:High-Throughput Screening Assays / Q000379:methods*; D051379:Mice; D012984:Software