Phase-locking of artificial neural oscillators can perform dynamic role binding and inferencing

Summary form only given, as follows. Previously, the authors have described a localist spreading-activation model, ROBIN (role binding and inferencing network), which uses stable, uniquely-identifying activation patterns, called signatures, to represent the dynamic role bindings critical for high-level natural language understanding tasks. A unique signature activation on a node represents a role binding, which can be propagated as activation across long paths of nodes to allow inferencing. The authors illustrate that metastable artificial neural oscillators can be used to implement signature activations. In this novel model, groups of relaxation oscillators with unique patterns of natural oscillation frequencies serve as signatures. Phase-locking of gated, interacting oscillators allows the signatures to be propagated dynamically across the network for inferencing. Paths of synchronized oscillators form a chain of role bindings representing the model´s plan/goal analysis of its natural language input.<>