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 sensory-motor 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.