A Winner-Takes-All Mechanism for Event Generation

-- We present a novel framework for central pattern generator design that leverages the intrinsic rebound excitability of neurons in combination with winner-takes-all computation. Our approach unifies decision-making and rhythmic pattern generation within a simple yet powerful network architecture that employs all-to-all inhibitory connections enhanced by designable excitatory interactions. This design offers significant advantages regarding ease of implementation, adaptability, and robustness. We demonstrate its efficacy through a ring oscillator model, which exhibits adaptive phase and frequency modulation, making the framework particularly promising for applications in neuromorphic systems and robotics. Central pattern generators provide a bio-inspired framework for locomotion control in robotics and neuromorphic systems by autonomously generating robust, rhythmic motor patterns. In many robotic applications [1]-[6], these approaches enable smooth gait generation, rapid adaptation to disturbances and varying terrains, and reduced computational overhead.