Open-Source Touchscreen-Equipped Operant Boxes: Custom-Built, Modular, and Affordable Systems for Modern Experimental Needs

Operant boxes are fundamental tools for studying animal behavior in laboratory settings. While commercial operant boxes offer standardized designs and software for immediate use, they come with significant drawbacks, including high start-up and maintenance costs, limited software flexibility, restricted experimental design options, time-intensive daily operation, and rigid data structures. The constraints posed by commercial operant boxes have constrained the scope and applications of animal research for decades. Custom-made operant boxes combat these limitations but historically have only been accessible to labs with dedicated engineering expertise and/or high budgets. The rise of accessible consumer electronic technologies like Raspberry Pi microcomputers, open-source software, and advanced search and inference tools (e.g., large language models) has made it feasible for non-experts to create cost-effective, customizable operant boxes. Recent projects have laid out their own blueprint designs for affordable open-source operant boxes, but many of these are simply proof-of-concept or isolated to specific experimental applications. We outline key considerations for custom designing versatile, low-cost, and robust multi-operant box systems by discussing our designs for a Raspberry Pi-powered pigeon operant box, equipped with touchscreen capabilities and modular stimulus control. This system features components sourced online, requires no specialized tools/skills (e.g., no soldering or intensive software for hardware interaction), and obviates the need for extended electrical engineering knowledge. Utilized hardware and software systems are highly adaptable, enabling precise customization for a wide range of tasks, behaviors, and experimental organisms. We also provide a streamlined framework for implementing cloud connectivity, version-controlled code design, automated data synchronization across multiple boxes using modern cloud platforms, and scalability for larger or smaller systems. Furthermore, this system costs a fraction (approximately 4%) of commercial alternatives. Our system's versatility is demonstrated through its application to diverse behavioral studies in pigeons, rats, humans, and even plants. Finally, we explore the integration of large language models for software development and troubleshooting, highlighting their potential to further simplify and enhance custom operant box systems.