Well designed behavioral experiments are vital to understand the complexities of neural coding, particularly as it becomes evident that such coding may be context-specific, highly distributed, and multiplexed. Traditional commercial solutions for behavioral setups, although available, often lack flexibility and comprehensive user control, and their high costs limit accessibility. Recognizing the necessity for rapid development and adaptability in behavioral experiments, we introduce here a novel cost-efficient, open-source system for controlling behavioral experiments that maintains the crucial aspects of reproducibility, monitoring, and control. At its core stands the Raspberry Pi Pico microcontroller (5 euro), which utilizes CircuitPython. This choice offers an accessible, easy-to-learn Python-based syntax, and supports a range of affordable hardware elements. Our system integrates effortlessly with synchronized video recording, digital and analog signal acquisition, all streamlined through user-friendly GUIs.To complement behavioral experiments with causal interrogation we designed a budget-friendly (<50 euros), modular and versatile laser-controller element for optogenetics, enabling precise control over various stimulation parameters of up to four lasers through an intuitive interface.We showcase the efficacy of our system with an implementation of a behavioral task for freely moving rats, whereby the animals have to dynamically adopt their strategy depending on the environmental state or external stimuli. Using modular and progressive training procedures, we demonstrate that rats can be proficiently trained in less than three weeks. This innovative system offers a flexible, modular approach for designing behavioral experiments, significantly reducing costs and enhancing scalability, thereby supporting a wide access to advanced experimental setups in neuroscientific research.