The roundworm C. elegans is a powerful model organism for dissecting the genetics of behavior and aging. The central genetic pathways regulating lifespan, such as insulin signaling, were first identified in worms. C. elegans is also the only animal for which a full map of all neural synpatic connections, or connectome, exists. However, current manual and automated methods are unable to efficiently monitor and quantify behavioral phenotypes which unfold over long time scales. Therefore, it has been difficult to study phenotypes such as long-term behavior states and behavioral changes with age in worms. To address these limitations, here I describe a novel device, called the WorMotel, to longitudinally monitor behavior in up to 240 single C. elegans on time scales encompassing the worm\u27s maximum lifespan of two months. The WorMotel is fabricated from polydimethylsiloxane from a 3-D printed negative mold. Each device consists of 240 individual wells, each of which houses a single worm atop agar and bacterial food. I use custom software to quantify movement between frames to longitudinally monitor behavior for each animal. I first describe the application of the WorMotel to the automation of lifespan measurements in C. elegans, the characterization of intra-strain and inter-strain variability in behavioral decline, the relationship between behavior and lifespan, and the scaling of behavioral decline with increasing stress. I then describe the application of the WorMotel to quantify locomotive behavioral states and their modulation by the presence or absence of food as well as biogenic amine neurotransmitters. Using the WorMotel in combination with genetics and pharmacology, I outline a neural circuit by which the biogenic amines serotonin and octopamine regulate locomotion state to signal animals to adopt behavior appropriate to a fed and fasting state, respectively. I include protocols for construction of custom imaging rigs and requirements for long-term imaging as an appendix. The WorMotel is a powerful tool that can facilitate discovery and understanding of the mechanisms underlying long-term phenotypes such as behavioral states and aging
