Neuromorphic design of a rhythmic network

Abstract

Central Pattern Generators (CPGs) have long inspired the design of rhythms that combine endogenous generation and exogenous interaction. In neurodynamics and engineering studies, CPGs have been primarily analysed and designed as networks of coupled oscillators. In contrast, the present article regards CPGs as networks that propagate events through excitable rather than oscillatory nodes. The proposed event-based perspective reduces the design of network-level rhythmic properties to the tuning of local nodal input-output characteristics. This reduction enables a distributed and robust design methodology: nodes can be tuned independently, they can be heterogeneous, and the global rhythm results from local event propagation rather than from a specific global tuning of the network parameters. The present article builds on previously introduced concepts that parallel existing characterizations of oscillators: the event describing function (eDF), which characterises the propagation delay of a node, and the event phase response curve (ePRC), which characterises the phase sensitivity of a node. Event-based CPGs made of excitable rather than oscillatory nodes emerge as a principled design framework for robust rhythm generation.