Theoretical implications of quantitative properties of interval timing and probability estimation in mouse and rat.

In three experiments with mice ( Mus musculus ) and rats (Rattus norvigicus), we used a switch paradigm to measure quantitative properties of the interval-timing mechanism. We found that: 1) Rodents adjusted the precision of their timed switches in response to changes in the interval between the short and long feed latencies (the temporal goalposts). 2) The variability in the timing of the switch response was reduced or unchanged in the face of large trial-to-trial random variability in the short and long feed latencies.

Automated, quantitative cognitive/behavioral screening of mice: for genetics, pharmacology, animal cognition and undergraduate instruction.

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.

Cognitive assessment of mice strains heterozygous for cell-adhesion genes reveals strain-specific alterations in timing.

We used a fully automated system for the behavioural measurement of physiologically meaningful properties of basic mechanisms of cognition to test two strains of heterozygous mutant mice, Bfc (batface) and L1, and their wild-type littermate controls. Both of the target genes are involved in the establishment and maintenance of synapses. We find that the Bfc heterozygotes show reduced precision in their representation of interval duration, whereas the L1 heterozygotes show increased precision.

Adapting without reinforcement.

Our data rule out a broad class of behavioral models in which behavioral change is guided by differential reinforcement. To demonstrate this, we showed that the number of reinforcers missed before the subject shifted its behavior was not sufficient to drive behavioral change. What's more, many subjects shifted their behavior to a more optimal strategy even when they had not yet missed a single reinforcer.

Mice take calculated risks.

Animals successfully navigate the world despite having only incomplete information about behaviorally important contingencies. It is an open question to what degree this behavior is driven by estimates of stochastic parameters (brain-constructed models of the experienced world) and to what degree it is directed by reinforcement-driven processes that optimize behavior in the limit without estimating stochastic parameters (model-free adaptation processes, such as associative learning). We find that mice adjust their behavior in response to a change in probability more quickly and abruptly than can be explained by differential reinforcement.