Measuring ingestive behavior of liquids in rodents is commonly used in studies of reward, metabolism, and circadian biology. Common approaches for measuring liquid intake in real time include computer-tethered lickometers or video-based systems. Additionally, liquids can be measured or weighed to determine the amount consumed without real-time sensing. Here, we built a photobeam-based sipper device that has the following advantages over traditional methods: (1) it is battery powered and fits in vivarium caging to allow home-cage measurements; (2) it quantifies the intake of two different liquids simultaneously for preference studies; (3) it is low cost and easily constructed, enabling high-throughput experiments; and (4) it is open source so that others can modify it to fit their experimental needs. We validated the performance of this device in three experiments. First, we calibrated our device using time-lapse video-based measurements of liquid intake and correlated sipper interactions with liquid intake. Second, we used the sipper device to measure preference for water versus chocolate milk, demonstrating its utility for two-bottle choice tasks. Third, we integrated the device with fiber photometry, establishing its utility for measuring neural activity in studies of ingestive behavior. This device requires no special equipment or caging, and is small, battery powered, and wireless, allowing it to be placed directly in rodent home cages. The total cost of fabrication is less than $100, and all design files and code are open source. Together, these factors greatly increase scalability and utility for a variety of behavioral neuroscience applications.
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http://dx.doi.org/10.1523/ENEURO.0292-19.2019 | DOI Listing |
Unlabelled: Free-choice paradigms such as two-bottle choice (2BC) are commonly used to characterize ethanol consumption and preference of rodent models used to study alcohol use disorder (AUD). However, these assays are limited by low temporal resolution that misses finer patterns of drinking behavior, including circadian drinking patterns that are known to vary with age and sex and are affected in AUD pathogenesis. Modern, cost-effective tools are becoming widely available that could elucidate these patterns, including open-source, Arduino-based home-cage sipper devices.
View Article and Find Full Text PDFeNeuro
July 2022
Departamento de Psicobiologia da Universidade Federal de São Paulo-UNIFESP, Rua Botucatu,862, Edificio de Ciencias Biomedicas, 1st floor, Sao Paulo, Zip Code: 04724-000, Brazil
Drinking behavior has been used in basic research to study metabolism, motivation, decision-making and different aspects of health problems, such as anhedonia and alcohol use disorders. In the majority of studies, liquid intake is measured by weighing the bottles before and after the experiment. This method does not tell much about the drinking microstructure, e.
View Article and Find Full Text PDFeNeuro
March 2020
Department of Anesthesiology, Washington University in St. Louis, St. Louis, Missouri 63108
Measuring ingestive behavior of liquids in rodents is commonly used in studies of reward, metabolism, and circadian biology. Common approaches for measuring liquid intake in real time include computer-tethered lickometers or video-based systems. Additionally, liquids can be measured or weighed to determine the amount consumed without real-time sensing.
View Article and Find Full Text PDFJ Am Assoc Lab Anim Sci
January 2013
Biologic Resources Laboratory, University of Illinois at Chicago, Chicago, Illinois, USA.
Providing high-quality, uncontaminated drinking water is an essential component of rodent husbandry. Acidification of drinking water is a common technique to control microbial growth but is not a benign treatment. In addition to its potential biologic effects, acidified water might interact with the water-delivery system, leading to the leaching of heavy metals into the drinking water.
View Article and Find Full Text PDFJ Neural Eng
June 2011
Department of Neurology, Northwestern University Chicago, IL 60611, USA.
Brain-machine interfaces (BMIs) use signals from the brain to control a device such as a computer cursor. Various types of signals have been used as BMI inputs, from single-unit action potentials to scalp potentials. Recently, intermediate-level signals such as subdural field potentials have also shown promise.
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