Dynamical Systems Account for Meta-level Cognition

The current paper studies possible neuronal mechanisms for meta-level cognition of rule switching. In contrast to the conventional approach of hand-designing the cognitive functions, our study employs evolutional processes to search for neuronal mechanisms accounting for meta-level cognitive functions required in the investigated robotic tasks. Our repeated simulation experiments showed that the different rules are embedded in separate self-organized attractors, while rule switching is enabled by the transitions among attractors. Furthermore, the results showed that although certain segregation between the lower sensorymotor level and the higher cognitive level enhance the task performance, meta-level cognition is significantly supported by the embodiment and the lower level sensory-motor properties.