Norbert Wiener and Nikolai Bernstein set the stage for a worldwide multidisciplinary attempt to understand how purposive action is integrated with cognition in a circular, bidirectional manner, both in life sciences and engineering. Such a ‘workshop’ is still open and far away from a satisfactory level of understanding, despite the current hype surrounding Artificial Intelligence (AI). The problem is that Cognition is frequently confused with Intelligence, overlooking a crucial distinction: the type of cognition that is required of a cognitive agent to meet the challenge of adaptive behavior in a changing environment is Embodied Cognition, which is antithetical to the disembodied and dualistic nature of the current wave of AI. This essay is the perspective formulation of a cybernetic framework for the representation of actions that, following Bernstein, is focused on what has long been considered the fundamental issue underlying action and motor control, namely the degrees of freedom problem. In particular, the paper reviews a solution to this problem based on a model of ideomotor/muscle-less synergy formation, namely the Passive Motion Paradigm (PMP). Moreover, it is shown how this modeling approach can be reformulated in a distributed manner based on a self-organizing neural paradigm consisting of multiple topology-representing networks with attractor dynamics. The computational implication of such an approach is also briefly analyzed looking at possible alternatives of the von Neuman paradigm, namely neuromorphic and quantum computing, aiming in perspective at a hybrid computational framework for integrating digital information, analog information, and quantum information. It is also suggested that such a framework is crucial not only for the neurobiological modeling of motor cognition but also for the design of the cognitive architecture of autonomous robots of industry 4.0 that are supposed to interact and communicate naturally with human partners.