Precise measurement of rodent drinking using CLiQR (Capacitive Lick Quantification in Rodents)

Accurate quantification of rodent licking behavior is essential for studies of fluid intake, including investigations of alcohol use disorder and obesity. Existing lickometry systems vary widely in sensing modality, cost, scalability, and data resolution, and many available systems either require specialized housing or store only binary lick/no lick data based on thresholding. Here we present CLiQR (Capacitive Lick Quantification in Rodents), an open-source capacitive lickometry system designed for high-throughput recording of licking behavior in home-cage environments while preserving the full capacitance time series. The system uses MPR121 capacitive sensors connected to custom metal-tipped serological pipette sippers and a centralized desktop computer to record data from up to 24 animals concurrently, with capacity for two-bottle choice experiments. Validation experiments demonstrated that the capacitive signals reliably distinguish licking from non-licking interactions. Total lick counts showed a strong positive correlation with measured fluid consumption (r = 0.827, p < 0.0001), confirming that detected events provide a meaningful proxy for intake. All information necessary to reproduce the system is shared openly in this manuscript and online. By combining scalability, full-trace data acquisition, and low cost, CLiQR provides a flexible and extensible platform for high-throughput behavioral neuroscience experiments and enables retrospective improvement of lick-detection algorithms. Significance StatementUnderstanding ingestive behavior requires measuring both total consumption and consumption pattern. Licking microstructure provides information about motivation, palatability, and behavioral strategies (i.e., binge-like front-loading); yet many existing lickometry systems are limited by high cost, low scalability, specialized housing requirements, or loss of information due to event-only data storage. We introduce CLiQR, an open-source capacitive lickometry system that enables high-throughput, home-cage recording from dozens of animals while preserving the full time series of capacitance data. By retaining raw data, CLiQR allows post hoc validation and reanalysis of licking behavior, addressing a key limitation of many current systems. This approach increases experimental flexibility, improves data transparency, and lowers barriers to large-scale studies of ingestive behavior.