A Winner-Takes-All Mechanism for Event Generation
This work addresses the problem of creating adaptable and robust rhythmic pattern generators for applications in neuromorphic systems and robotics, representing an incremental advancement in the field.
The paper tackles the design of central pattern generators by introducing a framework that combines rebound excitability and winner-takes-all computation, resulting in a network architecture that enables adaptive phase and frequency modulation in a ring oscillator model.
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.