The Motivation Network deals with the selection of action. It is realized as a recurrent neural network which forms local winner-take-all structures. The local competition allows for concurrent activation and decentralized control structures as required, e.g., for six legged walking. In the example case of six legged walking, it produces emergent stable and adaptive gaits.
Citation: Schilling, M., Paskarbeit, J., Hüffmeier, A., Schneider, A., Schmitz, J., and Cruse, H. (2013), “A hexapod walker using a heterarchical architecture for action selection”. Frontiers in Computational Neuroscience 7:126.